WorldWideScience

Sample records for chemical cluster methods

  1. New method for estimating clustering of DNA lesions induced by physical/chemical mutagens using fluorescence anisotropy.

    Science.gov (United States)

    Akamatsu, Ken; Shikazono, Naoya; Saito, Takeshi

    2017-11-01

    We have developed a new method for estimating the localization of DNA damage such as apurinic/apyrimidinic sites (APs) on DNA using fluorescence anisotropy. This method is aimed at characterizing clustered DNA damage produced by DNA-damaging agents such as ionizing radiation and genotoxic chemicals. A fluorescent probe with an aminooxy group (AlexaFluor488) was used to label APs. We prepared a pUC19 plasmid with APs by heating under acidic conditions as a model for damaged DNA, and subsequently labeled the APs. We found that the observed fluorescence anisotropy (r obs ) decreases as averaged AP density (λ AP : number of APs per base pair) increases due to homo-FRET, and that the APs were randomly distributed. We applied this method to three DNA-damaging agents, 60 Co γ-rays, methyl methanesulfonate (MMS), and neocarzinostatin (NCS). We found that r obs -λ AP relationships differed significantly between MMS and NCS. At low AP density (λ AP  < 0.001), the APs induced by MMS seemed to not be closely distributed, whereas those induced by NCS were remarkably clustered. In contrast, the AP clustering induced by 60 Co γ-rays was similar to, but potentially more likely to occur than, random distribution. This simple method can be used to estimate mutagenicity of ionizing radiation and genotoxic chemicals. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Weighted voting-based consensus clustering for chemical structure databases

    Science.gov (United States)

    Saeed, Faisal; Ahmed, Ali; Shamsir, Mohd Shahir; Salim, Naomie

    2014-06-01

    The cluster-based compound selection is used in the lead identification process of drug discovery and design. Many clustering methods have been used for chemical databases, but there is no clustering method that can obtain the best results under all circumstances. However, little attention has been focused on the use of combination methods for chemical structure clustering, which is known as consensus clustering. Recently, consensus clustering has been used in many areas including bioinformatics, machine learning and information theory. This process can improve the robustness, stability, consistency and novelty of clustering. For chemical databases, different consensus clustering methods have been used including the co-association matrix-based, graph-based, hypergraph-based and voting-based methods. In this paper, a weighted cumulative voting-based aggregation algorithm (W-CVAA) was developed. The MDL Drug Data Report (MDDR) benchmark chemical dataset was used in the experiments and represented by the AlogP and ECPF_4 descriptors. The results from the clustering methods were evaluated by the ability of the clustering to separate biologically active molecules in each cluster from inactive ones using different criteria, and the effectiveness of the consensus clustering was compared to that of Ward's method, which is the current standard clustering method in chemoinformatics. This study indicated that weighted voting-based consensus clustering can overcome the limitations of the existing voting-based methods and improve the effectiveness of combining multiple clusterings of chemical structures.

  3. Chemical graph-theoretic cluster expansions

    International Nuclear Information System (INIS)

    Klein, D.J.

    1986-01-01

    A general computationally amenable chemico-graph-theoretic cluster expansion method is suggested as a paradigm for incorporation of chemical structure concepts in a systematic manner. The cluster expansion approach is presented in a formalism general enough to cover a variety of empirical, semiempirical, and even ab initio applications. Formally such approaches for the utilization of chemical structure-related concepts may be viewed as discrete analogues of Taylor series expansions. The efficacy of the chemical structure concepts then is simply bound up in the rate of convergence of the cluster expansions. In many empirical applications, e.g., boiling points, chromatographic separation coefficients, and biological activities, this rate of convergence has been observed to be quite rapid. More note will be made here of quantum chemical applications. Relations to questions concerning size extensivity of energies and size consistency of wave functions are addressed

  4. Chemical Ligation: A Versatile Method for Nucleoside Modification with Boron Clusters

    Czech Academy of Sciences Publication Activity Database

    Wojtczak, B. A.; Andrysiak, A.; Grüner, Bohumír; Lesnikowski, Z. J.

    -, č. 14 (2008), s. 10675-10682 ISSN 0947-6539 R&D Projects: GA MŠk LC523 Grant - others:MSHE(PL) N405 051 32/3592; MSHE(PL) K152/H03/2007/10 Institutional research plan: CEZ:AV0Z40320502 Keywords : alkynes * azides * chemical ligation Subject RIV: CA - Inorganic Chemistry Impact factor: 5.454, year: 2008

  5. Voting-based consensus clustering for combining multiple clusterings of chemical structures

    Directory of Open Access Journals (Sweden)

    Saeed Faisal

    2012-12-01

    Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

  6. Chemical exposure and leukemia clusters

    International Nuclear Information System (INIS)

    Cartwright, R.A.

    1992-01-01

    This paper draws attention to the heterogeneous distribution of leukemia in childhood and in adults. The topic of cluster reports and generalized clustering is addressed. These issues are applied to what is known of the risk factor for both adult and childhood leukemia. Finally, the significance of parental occupational exposure and childhood leukemia is covered. (author). 23 refs

  7. Chemical Abundances of Giants in Globular Clusters

    Science.gov (United States)

    Gratton, Raffaele G.; Bragaglia, Angela; Carretta, Eugenio; D'Orazi, Valentina; Lucatello, Sara

    A large fraction of stars form in clusters. According to a widespread paradigma, stellar clusters are prototypes of single stellar populations. According to this concept, they formed on a very short time scale, and all their stars share the same chemical composition. Recently it has been understood that massive stellar clusters (the globular clusters) rather host various stellar populations, characterized by different chemical composition: these stellar populations have also slightly different ages, stars of the second generations being formed from the ejecta of part of those of an earlier one. Furthermore, it is becoming clear that the efficiency of the process is quite low: many more stars formed within this process than currently present in the clusters. This implies that a significant, perhaps even dominant fraction of the ancient population of galaxies formed within the episodes that lead to formation the globular clusters.

  8. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  9. Semi-supervised clustering methods.

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as "semi-supervised clustering" methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided.

  10. Semi-supervised clustering methods

    Science.gov (United States)

    Bair, Eric

    2013-01-01

    Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set. In many situations, however, information about the clusters is available in addition to the values of the features. For example, the cluster labels of some observations may be known, or certain observations may be known to belong to the same cluster. In other cases, one may wish to identify clusters that are associated with a particular outcome variable. This review describes several clustering algorithms (known as “semi-supervised clustering” methods) that can be applied in these situations. The majority of these methods are modifications of the popular k-means clustering method, and several of them will be described in detail. A brief description of some other semi-supervised clustering algorithms is also provided. PMID:24729830

  11. Cluster temperature. Methods for its measurement and stabilization

    International Nuclear Information System (INIS)

    Makarov, G N

    2008-01-01

    Cluster temperature is an important material parameter essential to many physical and chemical processes involving clusters and cluster beams. Because of the diverse methods by which clusters can be produced, excited, and stabilized, and also because of the widely ranging values of atomic and molecular binding energies (approximately from 10 -5 to 10 eV) and numerous energy relaxation channels in clusters, cluster temperature (internal energy) ranges from 10 -3 to about 10 8 K. This paper reviews research on cluster temperature and describes methods for its measurement and stabilization. The role of cluster temperature in and its influence on physical and chemical processes is discussed. Results on the temperature dependence of cluster properties are presented. The way in which cluster temperature relates to cluster structure and to atomic and molecular interaction potentials in clusters is addressed. Methods for strong excitation of clusters and channels for their energy relaxation are discussed. Some applications of clusters and cluster beams are considered. (reviews of topical problems)

  12. Medium Resolution Spectroscopy and Chemical Composition of Galactic Globular Clusters

    Directory of Open Access Journals (Sweden)

    Khamidullina D. A.

    2014-12-01

    Full Text Available We used integrated-light medium-resolution spectra of six Galactic globular clusters and model stellar atmospheres to carry out population synthesis and to derive chemical composition and age of the clusters. We used medium-resolution spectra of globular clusters published by Schiavon et al. (2005, as well as our long-slit observations with the 1.93 m telescope of the Haute Provence Observatory. The observed spectra were fitted to the theoretical ones interactively. As an initial approach, we used masses, radii and log g of stars in the clusters corresponding to the best fitting isochrones in the observed color-magnitude diagrams. The computed synthetic blanketed spectra of stars were summed according to the Chabrier mass function. To improve the determination of age and helium content, the shape and depth of the Balmer absorption lines was analysed. The abundances of Mg, Ca, C and several other elements were derived. A reasonable agreement with the literature data both in chemical composition and in age of the clusters is found. Our method might be useful for the development of stellar population models and for a better understanding of extragalactic star clusters.

  13. Medium resolution spectroscopy and chemical composition of Galactic globular clusters

    Science.gov (United States)

    Khamidullina, D. A.; Sharina, M. E.; Shimansky, V. V.; Davoust, E.

    We used integrated-light medium-resolution spectra of six Galactic globular clusters and model stellar atmospheres to carry out population synthesis and to derive chemical composition and age of the clusters. We used medium-resolution spectra of globular clusters published by Schiavon et al. (2005), as well as our long-slit observations with the 1.93 m telescope of the Haute Provence Observatory. The observed spectra were fitted to the theoretical ones interactively. As an initial approach, we used masses, radii and log g of stars in the clusters corresponding to the best fitting isochrones in the observed color-magnitude diagrams. The computed synthetic blanketed spectra of stars were summed according to the Chabrier mass function. To improve the determination of age and helium content, the shape and depth of the Balmer absorption lines was analysed. The abundances of Mg, Ca, C and several other elements were derived. A reasonable agreement with the literature data both in chemical composition and in age of the clusters is found. Our method might be useful for the development of stellar population models and for a better understanding of extragalactic star clusters.

  14. Application of the Fenske-Hall molecular orbital method to the calculation of 11B NMR chemical shifts. Antipodal substituent effects in deltahedral clusters

    International Nuclear Information System (INIS)

    Fehlner, T.P.; Czech, P.T.; Fenske, R.F.

    1990-01-01

    Utilizing Fenske-Hall wave functions and eigenvalues combined with the Ramsey sum over states (SOS) approximation, it is demonstrated that the sign and magnitude of the paramagnetic contribution to the shielding correlates well with the observed 11 B chemical shifts of a substantial variety of boron- and metal-containing compounds. Analysis of the molecular orbital (MO) contributions in the SOS approximation leads to an explanation of the large downfield shifts associated with metal-rich metallaboranes. A similar analysis demonstrates the importance of selected cluster occupied and unoccupied MO's in explaining both exo-cage substituent effects in which the antipodal boron resonance is shifted upfield and endo-cage substituent effects (interchange of isolobal fragments within the cage framework) in which the antipodal boron resonance is shifted downfield. Exo- and endo-cage substitution perturbs these MO's in an understandable fashion, leading to an internally consistent explanation of the observed chemical shift changes. 36 refs., 8 figs., 4 tabs

  15. Electronic and chemical properties of indium clusters

    International Nuclear Information System (INIS)

    Rayane, D.; Khardi, S.; Tribollet, B.; Broyer, M.; Melinon, P.; Cabaud, B.; Hoareau, A.

    1989-01-01

    Indium clusters are produced by the inert gas condensation technique. The ionization potentials are found higher for small clusters than for the Indium atom. This is explained by the p character of the bonding as in aluminium. Doubly charge clusters are also observed and fragmentation processes discussed. Finally small Indium clusters 3< n<9 are found very reactive with hydrocarbon. (orig.)

  16. Clustering methods for the optimization of atomic cluster structure

    Science.gov (United States)

    Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

    2018-04-01

    In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

  17. Blocked inverted indices for exact clustering of large chemical spaces.

    Science.gov (United States)

    Thiel, Philipp; Sach-Peltason, Lisa; Ottmann, Christian; Kohlbacher, Oliver

    2014-09-22

    The calculation of pairwise compound similarities based on fingerprints is one of the fundamental tasks in chemoinformatics. Methods for efficient calculation of compound similarities are of the utmost importance for various applications like similarity searching or library clustering. With the increasing size of public compound databases, exact clustering of these databases is desirable, but often computationally prohibitively expensive. We present an optimized inverted index algorithm for the calculation of all pairwise similarities on 2D fingerprints of a given data set. In contrast to other algorithms, it neither requires GPU computing nor yields a stochastic approximation of the clustering. The algorithm has been designed to work well with multicore architectures and shows excellent parallel speedup. As an application example of this algorithm, we implemented a deterministic clustering application, which has been designed to decompose virtual libraries comprising tens of millions of compounds in a short time on current hardware. Our results show that our implementation achieves more than 400 million Tanimoto similarity calculations per second on a common desktop CPU. Deterministic clustering of the available chemical space thus can be done on modern multicore machines within a few days.

  18. An investigation on the structure, spectroscopy and thermodynamic aspects of Br2((-))(H2O)n clusters using a conjunction of stochastic and quantum chemical methods.

    Science.gov (United States)

    Naskar, Pulak; Chaudhury, Pinaki

    2016-06-28

    In this work we obtained global as well as local structures of Br2((-))(H2O)n clusters for n = 2 to 6 followed by the study of IR-spectral features and thermochemistry for the structures. The way adopted by us to obtain structures is not the conventional one used in most cases. Here we at first generated excellent quality pre-optimized structures by exploring the suitable empirical potential energy surface using stochastic optimizer simulated annealing. These structures are then further refined using quantum chemical calculations to obtain the final structures, and spectral and thermodynamic features. We clearly showed that our approach results in very quick and better convergence which reduces the computational cost and obviously using the strategy we are able to get one [i.e. global] or more than one [i.e. global and local(s)] energetically lower structures than those which are already reported for a given cluster size. Moreover, IR-spectral results and the evolutionary trends in interaction energy, solvation energy and vertical detachment energy for global structures of each size have also been presented to establish the utility of the procedure employed.

  19. Chemical decontamination method

    International Nuclear Information System (INIS)

    Nishiwaki, Hitoshi.

    1996-01-01

    Metal wastes contaminated by radioactive materials are contained in a rotational decontamination vessel, and the metal wastes are rotated therein while being in contact with a slight amount of a decontamination liquid comprising a mineral acid. As the mineral acid, a mixed acid of nitric acid, hydrochloric acid and fluoric acid is preferably used. Alternatively, chemical decontamination can also be conducted by charging an acid resistant stirring medium in the rotational decontamination vessel. The surface of the metal wastes is uniformly covered by the slight amount of decontamination liquid to dissolve the surface layer. In addition, heat of dissolution generated in this case is accumulated in the inside of the rotational decontamination vessel, the temperature is elevated with no particular heating, thereby enabling to obtain an excellent decontamination effect substantially at the same level as in the case of heating the liquid to 70degC in a conventional immersion decontamination method. Further, although contact areas between the metal wastes and the immersion vessel are difficult to be decontaminated in the immersion decontamination method, all of areas can be dissolved uniformly in the present invention. (T.M.)

  20. The GALAH survey: chemical tagging of star clusters and new members in the Pleiades

    Science.gov (United States)

    Kos, Janez; Bland-Hawthorn, Joss; Freeman, Ken; Buder, Sven; Traven, Gregor; De Silva, Gayandhi M.; Sharma, Sanjib; Asplund, Martin; Duong, Ly; Lin, Jane; Lind, Karin; Martell, Sarah; Simpson, Jeffrey D.; Stello, Dennis; Zucker, Daniel B.; Zwitter, Tomaž; Anguiano, Borja; Da Costa, Gary; D'Orazi, Valentina; Horner, Jonathan; Kafle, Prajwal R.; Lewis, Geraint; Munari, Ulisse; Nataf, David M.; Ness, Melissa; Reid, Warren; Schlesinger, Katie; Ting, Yuan-Sen; Wyse, Rosemary

    2018-02-01

    The technique of chemical tagging uses the elemental abundances of stellar atmospheres to 'reconstruct' chemically homogeneous star clusters that have long since dispersed. The GALAH spectroscopic survey - which aims to observe one million stars using the Anglo-Australian Telescope - allows us to measure up to 30 elements or dimensions in the stellar chemical abundance space, many of which are not independent. How to find clustering reliably in a noisy high-dimensional space is a difficult problem that remains largely unsolved. Here, we explore t-distributed stochastic neighbour embedding (t-SNE) - which identifies an optimal mapping of a high-dimensional space into fewer dimensions - whilst conserving the original clustering information. Typically, the projection is made to a 2D space to aid recognition of clusters by eye. We show that this method is a reliable tool for chemical tagging because it can: (i) resolve clustering in chemical space alone, (ii) recover known open and globular clusters with high efficiency and low contamination, and (iii) relate field stars to known clusters. t-SNE also provides a useful visualization of a high-dimensional space. We demonstrate the method on a data set of 13 abundances measured in the spectra of 187 000 stars by the GALAH survey. We recover seven of the nine observed clusters (six globular and three open clusters) in chemical space with minimal contamination from field stars and low numbers of outliers. With chemical tagging, we also identify two Pleiades supercluster members (which we confirm kinematically), one as far as 6° - one tidal radius away from the cluster centre.

  1. Chemisorption on size-selected metal clusters: activation barriers and chemical reactions for deuterium and aluminum cluster ions

    International Nuclear Information System (INIS)

    Jarrold, M.F.; Bower, J.E.

    1988-01-01

    The authors describe a new approach to investigating chemisorption on size-selected metal clusters. This approach involves investigating the collision-energy dependence of chemisorption using low-energy ion beam techniques. The method provides a direct measure of the activation barrier for chemisorption and in some cases an estimate of the desorption energy as well. They describe the application of this technique to chemisorption of deuterium on size-selected aluminum clusters. The activation barriers increase with cluster size (from a little over 1 eV for Al 10 + to around 2 eV for Al 27 + ) and show significant odd-even oscillations. The activation barriers for the clusters with an odd number of atoms are larger than those for the even-numbered clusters. In addition to chemisorption of deuterium onto the clusters, chemical reactions were observed, often resulting in cluster fragmentation. The main products observed were Al/sub n-1/D + , Al/sub n-2/ + , and Al + for clusters with n + and Al/sub n-1/D + for the larger clusters

  2. Comparing the performance of biomedical clustering methods

    DEFF Research Database (Denmark)

    Wiwie, Christian; Baumbach, Jan; Röttger, Richard

    2015-01-01

    expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

  3. The polarizable embedding coupled cluster method

    DEFF Research Database (Denmark)

    Sneskov, Kristian; Schwabe, Tobias; Kongsted, Jacob

    2011-01-01

    We formulate a new combined quantum mechanics/molecular mechanics (QM/MM) method based on a self-consistent polarizable embedding (PE) scheme. For the description of the QM region, we apply the popular coupled cluster (CC) method detailing the inclusion of electrostatic and polarization effects...

  4. Dealing with chemical reaction pathways and electronic excitations in molecular systems via renormalized and active-space coupled-cluster methods

    Energy Technology Data Exchange (ETDEWEB)

    Piecuch, Piotr; Li, Wei; Lutz, Jesse J. [Department of Chemistry, Michigan State University, East Lansing, MI 48824 (United States); Włoch, Marta [Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931 (United States); Gour, Jeffrey R. [Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA and Department of Chemistry, Stanford University, Stanford, California 94305 (United States)

    2015-01-22

    Coupled-cluster (CC) theory has become the de facto standard for high-accuracy molecular calculations, but the widely used CC and equation-of-motion (EOM) CC approaches, such as CCSD(T) and EOMCCSD, have difficulties with capturing stronger electron correlations that characterize multi-reference molecular problems. This presentation demonstrates that many of these difficulties can be addressed by exploiting the completely renormalized (CR) CC and EOMCC approaches, such as CR-CC(2,3), CR-EOMCCSD(T), and CR-EOMCC(2,3), and their local correlation counterparts applicable to systems with hundreds of atoms, and the active-space CC/EOMCC approaches, such as CCSDt and EOMCCSDt, and their extensions to valence systems via the electron-attached and ionized formalisms.

  5. METHOD OF CONSTRUCTION OF GENETIC DATA CLUSTERS

    Directory of Open Access Journals (Sweden)

    N. A. Novoselova

    2016-01-01

    Full Text Available The paper presents a method of construction of genetic data clusters (functional modules using the randomized matrices. To build the functional modules the selection and analysis of the eigenvalues of the gene profiles correlation matrix is performed. The principal components, corresponding to the eigenvalues, which are significantly different from those obtained for the randomly generated correlation matrix, are used for the analysis. Each selected principal component forms gene cluster. In a comparative experiment with the analogs the proposed method shows the advantage in allocating statistically significant different-sized clusters, the ability to filter non- informative genes and to extract the biologically interpretable functional modules matching the real data structure.

  6. Blocked inverted indices for exact clustering of large chemical spaces

    NARCIS (Netherlands)

    Thiel, P.; Sach-Peltason, L.; Ottmann, C.; Kohlbacher, O.

    2014-01-01

    The calculation of pairwise compound similarities based on fingerprints is one of the fundamental tasks in chemoinformatics. Methods for efficient calculation of compound similarities are of utmost importance for various applications like similarity searching or library clustering. With the

  7. Chemical control methods and tools

    Science.gov (United States)

    Steven Manning; James. Miller

    2011-01-01

    After determining the best course of action for control of an invasive plant population, it is important to understand the variety of methods available to the integrated pest management professional. A variety of methods are now widely used in managing invasive plants in natural areas, including chemical, mechanical, and cultural control methods. Once the preferred...

  8. Radionuclide identification using subtractive clustering method

    International Nuclear Information System (INIS)

    Farias, Marcos Santana; Mourelle, Luiza de Macedo

    2011-01-01

    Radionuclide identification is crucial to planning protective measures in emergency situations. This paper presents the application of a method for a classification system of radioactive elements with a fast and efficient response. To achieve this goal is proposed the application of subtractive clustering algorithm. The proposed application can be implemented in reconfigurable hardware, a flexible medium to implement digital hardware circuits. (author)

  9. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

    Science.gov (United States)

    Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

    2016-08-01

    The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

  10. Chemical microreactor and method thereof

    Science.gov (United States)

    Morse, Jeffrey D [Martinez, CA; Jankowski, Alan [Livermore, CA

    2011-08-09

    A method for forming a chemical microreactor includes forming at least one capillary microchannel in a substrate having at least one inlet and at least one outlet, integrating at least one heater into the chemical microreactor, interfacing the capillary microchannel with a liquid chemical reservoir at the inlet of the capillary microchannel, and interfacing the capillary microchannel with a porous membrane near the outlet of the capillary microchannel, the porous membrane being positioned beyond the outlet of the capillary microchannel, wherein the porous membrane has at least one catalyst material imbedded therein.

  11. Chemical abundances of globular clusters in NGC 5128 (Centaurus A)

    Science.gov (United States)

    Hernandez, Svea; Larsen, Søren; Trager, Scott; Kaper, Lex; Groot, Paul

    2018-06-01

    We perform a detailed abundance analysis on integrated-light spectra of 20 globular clusters (GCs) in the early-type galaxy NGC 5128 (Centaurus A). The GCs were observed with X-Shooter on the Very Large Telescope (VLT). The cluster sample spans a metallicity range of -1.92 poor GCs in NGC 5128 is genuine, it could hint at a chemical enrichment history different than that experienced by the MW. We also measure Na abundances in 9 out of 20 GCs. We find evidence for intracluster abundance variations in six of these clusters where we see enhanced [Na/Fe] > +0.25 dex. We obtain the first abundance measurements of Cr, Mn, and Ni for a sample of the GC population in NGC 5128 and find consistency with the overall trends observed in the MW, with a slight enhancement (<0.1 dex) in the Fe-peak abundances measured in the NGC 5128.

  12. Chemical probes of metal cluster structure--Fe, Co, Ni, and Cu

    International Nuclear Information System (INIS)

    Parks, E.K.; Zhu, L.; Ho, J.; Riley, S.J.

    1992-01-01

    Chemical reactivity is one of the few methods currently available for investigating the geometrical structure of isolated transition metal clusters. In this paper we summarize what is currently known about the structures of clusters of four transition metals, Fe, Co, Ni, and Cu, in the size range from 13 to 180 atoms. Chemical probes used to determine structural information include reactions with H 2 (D 2 ), H 2 0, NH 3 and N 2 . Measurements at both low coverage and at saturation are discussed

  13. Recent advances in coupled-cluster methods

    CERN Document Server

    Bartlett, Rodney J

    1997-01-01

    Today, coupled-cluster (CC) theory has emerged as the most accurate, widely applicable approach for the correlation problem in molecules. Furthermore, the correct scaling of the energy and wavefunction with size (i.e. extensivity) recommends it for studies of polymers and crystals as well as molecules. CC methods have also paid dividends for nuclei, and for certain strongly correlated systems of interest in field theory.In order for CC methods to have achieved this distinction, it has been necessary to formulate new, theoretical approaches for the treatment of a variety of essential quantities

  14. Comparing Chemical Compositions of Dwarf Elliptical Galaxies and Globular Clusters

    Science.gov (United States)

    Chu, Jason; Sparkman, Lea; Toloba, Elisa; Guhathakurta, Puragra

    2015-01-01

    Because of their abundance in cluster environments and fragility due to their low mass, dwarf elliptical galaxies (dEs) are excellent specimens for studying the physical processes that occur inside galaxy clusters. These studies can be used to expand our understanding of the process of galaxy (specifically dE) formation and the role of dark matter in the Universe. To move closer to better understanding these topics, we present a study of the relationship between dEs and globular clusters (GCs) by using the largest sample of dEs and GC satellites to date. We focus on comparing the ages and chemical compositions of dE nuclei with those of satellite GCs by analyzing absorption lines in their spectra. To better view the spectral features of these relatively dim objects, we employ a spectral co-addition process, where we add the fluxes of several objects to produce a single spectrum with high signal-to-noise ratio. Our finding that dE nuclei are younger and more metal rich than globular clusters establishes important benchmarks that future dE formation theories will consider. We also establish a means to identify GCs whose parent galaxies are uncertain, which allows us to make comparisons between this GC group and the satellite GCs.

  15. Chemically induced magnetism in atomically precise gold clusters.

    Science.gov (United States)

    Krishna, Katla Sai; Tarakeshwar, Pilarisetty; Mujica, Vladimiro; Kumar, Challa S S R

    2014-03-12

    Comparative theoretical and experimental investigations are reported into chemically induced magnetism in atomically-precise, ligand-stabilized gold clusters Au25 , Au38 and Au55 . The results indicate that [Au25 (PPh3 )10 (SC12 H25 )5 Cl2 ](2+) and Au38 (SC12 H25 )24 are diamagnetic, Au25 (SC2 H4 Ph)18 is paramagnetic, and Au55 (PPh3 )12 Cl6 , is ferromagnetic at room temperature. Understanding the magnetic properties resulting from quantum size effects in such atomically precise gold clusters could lead to new fundamental discoveries and applications. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Electronic and chemical properties of barium and indium clusters

    International Nuclear Information System (INIS)

    Onwuagba, B.N.

    1992-11-01

    The ground state electronic and chemical properties of divalent barium and trivalent indium are investigated in a self-consistent manner using the spin-polarized local density approximation in the framework of Density Functional Theory. A jellium model is adopted in the spirit of Gunnarsson and Lundqvist exchange and correlation energies and the calculated properties primarily associated with the s-p orbitals in barium and p orbitals in indium provide deepened insight towards the understanding of the mechanisms to the magic numbers in both clusters. (author). 21 refs, 5 figs

  17. Membership determination of open clusters based on a spectral clustering method

    Science.gov (United States)

    Gao, Xin-Hua

    2018-06-01

    We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

  18. Hybrid Tracking Algorithm Improvements and Cluster Analysis Methods.

    Science.gov (United States)

    1982-02-26

    UPGMA ), and Ward’s method. Ling’s papers describe a (k,r) clustering method. Each of these methods have individual characteristics which make them...Reference 7), UPGMA is probably the most frequently used clustering strategy. UPGMA tries to group new points into an existing cluster by using an

  19. MANNER OF STOCKS SORTING USING CLUSTER ANALYSIS METHODS

    Directory of Open Access Journals (Sweden)

    Jana Halčinová

    2014-06-01

    Full Text Available The aim of the present article is to show the possibility of using the methods of cluster analysis in classification of stocks of finished products. Cluster analysis creates groups (clusters of finished products according to similarity in demand i.e. customer requirements for each product. Manner stocks sorting of finished products by clusters is described a practical example. The resultants clusters are incorporated into the draft layout of the distribution warehouse.

  20. Molecular cluster theory of chemical bonding in actinide oxide

    International Nuclear Information System (INIS)

    Ellis, D.E.; Gubanov, V.A.; Rosen, A.

    1978-01-01

    The electronic structure of actinide monoxides AcO and dioxides AcO 2 , where Ac = Th, U, Np, Pu, Am, Cm and Bk has been studied by molecular cluster methods based on the first-principles one-electron local density theory. Molecular orbitals for nearest neighbor clusters AcO 10- 6 and AcO 12- 8 representative of monoxide and dioxide lattices were obtained using non-relativistic spin-restricted and spin-polarized Hartree-Fock-Slater models for the entire series. Fully relativistic Dirac-Slater calculations were performed for ThO, UO and NpO in order to explore magnitude of spin-orbit splittings and level shifts in valence structure. Self-consistent iterations were carried out for NpO, in which the NpO 6 cluster was embedded in the molecular field of the solid. Finally, a ''moment polarized'' model which combines both spin-polarization and relativistic effects in a consistent fashion was applied to the NpO system. Covalent mixing of oxygen 2p and Ac 5f orbitals was found to increase rapidly across the actinide series; metal s,p,d covalency was found to be nearly constant. Mulliken atomic population analysis of cluster eigenvectors shows that free-ion crystal field models are unreliable, except for the light actinides. X-ray photoelectron line shapes have been calculated and are found to compare rather well with experimental data on the dioxides

  1. Recent developments of the quantum chemical cluster approach for modeling enzyme reactions.

    Science.gov (United States)

    Siegbahn, Per E M; Himo, Fahmi

    2009-06-01

    The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

  2. Clustering Methods Application for Customer Segmentation to Manage Advertisement Campaign

    OpenAIRE

    Maciej Kutera; Mirosława Lasek

    2010-01-01

    Clustering methods are recently so advanced elaborated algorithms for large collection data analysis that they have been already included today to data mining methods. Clustering methods are nowadays larger and larger group of methods, very quickly evolving and having more and more various applications. In the article, our research concerning usefulness of clustering methods in customer segmentation to manage advertisement campaign is presented. We introduce results obtained by using four sel...

  3. Integrated management of thesis using clustering method

    Science.gov (United States)

    Astuti, Indah Fitri; Cahyadi, Dedy

    2017-02-01

    Thesis is one of major requirements for student in pursuing their bachelor degree. In fact, finishing the thesis involves a long process including consultation, writing manuscript, conducting the chosen method, seminar scheduling, searching for references, and appraisal process by the board of mentors and examiners. Unfortunately, most of students find it hard to match all the lecturers' free time to sit together in a seminar room in order to examine the thesis. Therefore, seminar scheduling process should be on the top of priority to be solved. Manual mechanism for this task no longer fulfills the need. People in campus including students, staffs, and lecturers demand a system in which all the stakeholders can interact each other and manage the thesis process without conflicting their timetable. A branch of computer science named Management Information System (MIS) could be a breakthrough in dealing with thesis management. This research conduct a method called clustering to distinguish certain categories using mathematics formulas. A system then be developed along with the method to create a well-managed tool in providing some main facilities such as seminar scheduling, consultation and review process, thesis approval, assessment process, and also a reliable database of thesis. The database plays an important role in present and future purposes.

  4. Cluster chemical ionization for improved confidence level in sample identification by gas chromatography/mass spectrometry.

    Science.gov (United States)

    Fialkov, Alexander B; Amirav, Aviv

    2003-01-01

    Upon the supersonic expansion of helium mixed with vapor from an organic solvent (e.g. methanol), various clusters of the solvent with the sample molecules can be formed. As a result of 70 eV electron ionization of these clusters, cluster chemical ionization (cluster CI) mass spectra are obtained. These spectra are characterized by the combination of EI mass spectra of vibrationally cold molecules in the supersonic molecular beam (cold EI) with CI-like appearance of abundant protonated molecules, together with satellite peaks corresponding to protonated or non-protonated clusters of sample compounds with 1-3 solvent molecules. Like CI, cluster CI preferably occurs for polar compounds with high proton affinity. However, in contrast to conventional CI, for non-polar compounds or those with reduced proton affinity the cluster CI mass spectrum converges to that of cold EI. The appearance of a protonated molecule and its solvent cluster peaks, plus the lack of protonation and cluster satellites for prominent EI fragments, enable the unambiguous identification of the molecular ion. In turn, the insertion of the proper molecular ion into the NIST library search of the cold EI mass spectra eliminates those candidates with incorrect molecular mass and thus significantly increases the confidence level in sample identification. Furthermore, molecular mass identification is of prime importance for the analysis of unknown compounds that are absent in the library. Examples are given with emphasis on the cluster CI analysis of carbamate pesticides, high explosives and unknown samples, to demonstrate the usefulness of Supersonic GC/MS (GC/MS with supersonic molecular beam) in the analysis of these thermally labile compounds. Cluster CI is shown to be a practical ionization method, due to its ease-of-use and fast instrumental conversion between EI and cluster CI, which involves the opening of only one valve located at the make-up gas path. The ease-of-use of cluster CI is analogous

  5. Integration K-Means Clustering Method and Elbow Method For Identification of The Best Customer Profile Cluster

    Science.gov (United States)

    Syakur, M. A.; Khotimah, B. K.; Rochman, E. M. S.; Satoto, B. D.

    2018-04-01

    Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects. SMEs Indonesia has a variety of customers, but SMEs do not have the mapping of these customers so they did not know which customers are loyal or otherwise. Customer mapping is a grouping of customer profiling to facilitate analysis and policy of SMEs in the production of goods, especially batik sales. Researchers will use a combination of K-Means method with elbow to improve efficient and effective k-means performance in processing large amounts of data. K-Means Clustering is a localized optimization method that is sensitive to the selection of the starting position from the midpoint of the cluster. So choosing the starting position from the midpoint of a bad cluster will result in K-Means Clustering algorithm resulting in high errors and poor cluster results. The K-means algorithm has problems in determining the best number of clusters. So Elbow looks for the best number of clusters on the K-means method. Based on the results obtained from the process in determining the best number of clusters with elbow method can produce the same number of clusters K on the amount of different data. The result of determining the best number of clusters with elbow method will be the default for characteristic process based on case study. Measurement of k-means value of k-means has resulted in the best clusters based on SSE values on 500 clusters of batik visitors. The result shows the cluster has a sharp decrease is at K = 3, so K as the cut-off point as the best cluster.

  6. The incidence of chemically peculiar stars in open clusters

    Energy Technology Data Exchange (ETDEWEB)

    Netopil, M.

    2013-07-01

    The formation and evolution of chemically peculiar (CP) stars is still a matter of debate, although the first representatives were detected already more than 110 years ago. From the astrophysical point of view, these objects are of particular interest, since they combine a wide variety of specific properties. This work deals with a subgroup of CP stars, showing beside overabundances of some iron-peak (e.g. Chromium) and rare earth elements like Europium, also strong ordered magnetic fields as well as a slow rotation. Based on a selection of well investigated close field stars, the possible connections of these properties were examined. However, the main research focus was the analysis of a relationship between the number of CP stars and their age. For this purpose, the results of the extensive Delta-a survey in open clusters were used. This photometric filter system allows an efficient and economic detection of magnetic CP stars due to a characteristic flux depression at 520 nm. Compared to field stars, open clusters offer the big advantage that for example the age and the distance can be determined more accurately on a statistical basis, since all member stars of an open cluster originate more or less at the same time from a single molecular cloud. After the membership analysis of all in Delta a investigated objects and the determination of the cluster parameters, it was shown that the occurrence of CP stars depend on age, but can be explained by the general evolution of stars. This entails amongst others that CP stars show their typical characteristics already as soon as they have arrived the main-sequence, or even before. Furthermore, we were able to detect at least one representative, probably still in its pre-main-sequence phase. (author) [German] Die Entstehung und Entwicklung von chemisch pekuliaren (CP) Sternen ist nach wie vor nicht restlos geklärt, und das obwohl die ersten Vertreter dieser Sterngruppe bereits vor mehr als 110 Jahren entdeckt wurden. Aus

  7. Homological methods, representation theory, and cluster algebras

    CERN Document Server

    Trepode, Sonia

    2018-01-01

    This text presents six mini-courses, all devoted to interactions between representation theory of algebras, homological algebra, and the new ever-expanding theory of cluster algebras. The interplay between the topics discussed in this text will continue to grow and this collection of courses stands as a partial testimony to this new development. The courses are useful for any mathematician who would like to learn more about this rapidly developing field; the primary aim is to engage graduate students and young researchers. Prerequisites include knowledge of some noncommutative algebra or homological algebra. Homological algebra has always been considered as one of the main tools in the study of finite-dimensional algebras. The strong relationship with cluster algebras is more recent and has quickly established itself as one of the important highlights of today’s mathematical landscape. This connection has been fruitful to both areas—representation theory provides a categorification of cluster algebras, wh...

  8. CCM: A Text Classification Method by Clustering

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    In this paper, a new Cluster based Classification Model (CCM) for suspicious email detection and other text classification tasks, is presented. Comparative experiments of the proposed model against traditional classification models and the boosting algorithm are also discussed. Experimental results...... show that the CCM outperforms traditional classification models as well as the boosting algorithm for the task of suspicious email detection on terrorism domain email dataset and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. The overall finding is that applying a cluster based...

  9. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

  10. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  11. Method for producing chemical energy

    Science.gov (United States)

    Jorgensen, Betty S.; Danen, Wayne C.

    2004-09-21

    Fluoroalkylsilane-coated metal particles having a central metal core, a buffer layer surrounding the core, and a fluoroalkylsilane layer attached to the buffer layer are prepared by combining a chemically reactive fluoroalkylsilane compound with an oxide coated metal particle having a hydroxylated surface. The resulting fluoroalkylsilane layer that coats the particles provides them with excellent resistance to aging. The particles can be blended with oxidant particles to form energetic powder that releases chemical energy when the buffer layer is physically disrupted so that the reductant metal core can react with the oxidant.

  12. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    Science.gov (United States)

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  13. A Web service substitution method based on service cluster nets

    Science.gov (United States)

    Du, YuYue; Gai, JunJing; Zhou, MengChu

    2017-11-01

    Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

  14. Fuzzy C-means method for clustering microarray data.

    Science.gov (United States)

    Dembélé, Doulaye; Kastner, Philippe

    2003-05-22

    Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

  15. Progeny Clustering: A Method to Identify Biological Phenotypes

    Science.gov (United States)

    Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

    2015-01-01

    Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

  16. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng [Jiangnan University, Wuxi (China)

    2014-11-15

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy.

  17. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    International Nuclear Information System (INIS)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng

    2014-01-01

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy

  18. THERMAL AND CHEMICAL EVOLUTIONS OF GALAXY CLUSTERS OBSERVED WITH SUZAKU

    Directory of Open Access Journals (Sweden)

    Kosuke Sato

    2013-12-01

    Full Text Available We studied the properties of the intracluster medium (ICM of galaxy clusters to outer regions observed with Suzaku. The observed temperature dropped by about ~30% from the central region to the virial radius of the clusters. The derived entropy profile agreed with the expectation from simulations within r500, while the entropy profile in r > r500 indicated a flatter slope than the simulations. This would suggest that the cluster outskirts were out of hydrostatic equilibrium. As for the metallicity, we studied the metal abundances from O to Fe up to ~0.5 times the virial radius of galaxy groups and clusters. Comparing the results with supernova nucleosynthesis models, the number ratio of type II to Ia supernovae is estimated to be ~3.5. We also calculated not only Fe, but also O and Mg mass-to-light ratios (MLRs with K-band luminosity. The MLRs in the clusters had a similar feature.

  19. The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

    Science.gov (United States)

    Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

    2017-07-01

    Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

  20. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    Anderson, Ryan B.; Bell, James F.; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.

    2012-01-01

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO 2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ∼ 3 wt.%. The statistical significance of these improvements was ∼ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically

  1. A Latent Variable Clustering Method for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Vasilev, Vladislav; Iliev, Georgi; Poulkov, Vladimir

    2016-01-01

    In this paper we derive a clustering method based on the Hidden Conditional Random Field (HCRF) model in order to maximizes the performance of a wireless sensor. Our novel approach to clustering in this paper is in the application of an index invariant graph that we defined in a previous work and...

  2. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  3. Cluster dynamics transcending chemical dynamics toward nuclear fusion.

    Science.gov (United States)

    Heidenreich, Andreas; Jortner, Joshua; Last, Isidore

    2006-07-11

    Ultrafast cluster dynamics encompasses femtosecond nuclear dynamics, attosecond electron dynamics, and electron-nuclear dynamics in ultraintense laser fields (peak intensities 10(15)-10(20) W.cm(-2)). Extreme cluster multielectron ionization produces highly charged cluster ions, e.g., (C(4+)(D(+))(4))(n) and (D(+)I(22+))(n) at I(M) = 10(18) W.cm(-2), that undergo Coulomb explosion (CE) with the production of high-energy (5 keV to 1 MeV) ions, which can trigger nuclear reactions in an assembly of exploding clusters. The laser intensity and the cluster size dependence of the dynamics and energetics of CE of (D(2))(n), (HT)(n), (CD(4))(n), (DI)(n), (CD(3)I)(n), and (CH(3)I)(n) clusters were explored by electrostatic models and molecular dynamics simulations, quantifying energetic driving effects, and kinematic run-over effects. The optimization of table-top dd nuclear fusion driven by CE of deuterium containing heteroclusters is realized for light-heavy heteroclusters of the largest size, which allows for the prevalence of cluster vertical ionization at the highest intensity of the laser field. We demonstrate a 7-orders-of-magnitude enhancement of the yield of dd nuclear fusion driven by CE of light-heavy heteroclusters as compared with (D(2))(n) clusters of the same size. Prospective applications for the attainment of table-top nucleosynthesis reactions, e.g., (12)C(P,gamma)(13)N driven by CE of (CH(3)I)(n) clusters, were explored.

  4. Clustering Methods Application for Customer Segmentation to Manage Advertisement Campaign

    Directory of Open Access Journals (Sweden)

    Maciej Kutera

    2010-10-01

    Full Text Available Clustering methods are recently so advanced elaborated algorithms for large collection data analysis that they have been already included today to data mining methods. Clustering methods are nowadays larger and larger group of methods, very quickly evolving and having more and more various applications. In the article, our research concerning usefulness of clustering methods in customer segmentation to manage advertisement campaign is presented. We introduce results obtained by using four selected methods which have been chosen because their peculiarities suggested their applicability to our purposes. One of the analyzed method k-means clustering with random selected initial cluster seeds gave very good results in customer segmentation to manage advertisement campaign and these results were presented in details in the article. In contrast one of the methods (hierarchical average linkage was found useless in customer segmentation. Further investigations concerning benefits of clustering methods in customer segmentation to manage advertisement campaign is worth continuing, particularly that finding solutions in this field can give measurable profits for marketing activity.

  5. Chemical methods of rock analysis

    National Research Council Canada - National Science Library

    Jeffery, P. G; Hutchison, D

    1981-01-01

    .... Such methods include those based upon spectrophotometry, flame emission spectrometry and atomic absorption spectroscopy, as well as gravimetry, titrimetry and the use of ion-selective electrodes...

  6. Survey of Nuclear Methods in Chemical Technology

    International Nuclear Information System (INIS)

    Broda, E.

    1966-01-01

    An attempt is made to classify nuclear methods on a logical basis to facilitate assimilation by the technologist. The three main groups are: (I) Tracer methods, (II) Methods based on the influence of absorbers on radiations to be measured, and (III) Radiation chemical methods. The variants of the first two groups are discussed in some detail, and typical examples are given. Group I can be subdivided into (1) Indicator methods, (2) Emanation methods, (3) Radioreagent methods, and (4) Isotope dilution methods, Group II into (5) Activation methods, (6) Absorption methods, (7) Induced Nuclear Reaction methods, (8) Scattering methods, and (9) Fluorescence methods. While the economic benefits due to nuclear methods already run into hundreds of millions of dollars annually, owing to radiation protection problems radiochemical methods in the strict sense are not widely used in actual production. It is suggested that more use should be made of pilot plant tracer studies of chemical processes as used in industry. (author)

  7. Chemical methods of rock analysis

    National Research Council Canada - National Science Library

    Jeffery, P. G; Hutchison, D

    1981-01-01

    A practical guide to the methods in general use for the complete analysis of silicate rock material and for the determination of all those elements present in major, minor or trace amounts in silicate...

  8. Shaping a novel security approach in chemical industrial clusters to prevent large-scale domino events

    NARCIS (Netherlands)

    Reniers, Genserik L L; Dullaert, Wout; Soudan, Karel

    2009-01-01

    Two aspects are important when it comes to guaranteeing an effective and efficient security policy in a chemical industrial cluster. The first issue involves obtaining an acceptable level of collaboration between the different enterprises forming the cluster. The second topic is to ensure that an

  9. Chemical Tracer Methods: Chapter 7

    Science.gov (United States)

    Healy, Richard W.

    2017-01-01

    Tracers have a wide variety of uses in hydrologic studies: providing quantitative or qualitative estimates of recharge, identifying sources of recharge, providing information on velocities and travel times of water movement, assessing the importance of preferential flow paths, providing information on hydrodynamic dispersion, and providing data for calibration of water flow and solute-transport models (Walker, 1998; Cook and Herczeg, 2000; Scanlon et al., 2002b). Tracers generally are ions, isotopes, or gases that move with water and that can be detected in the atmosphere, in surface waters, and in the subsurface. Heat also is transported by water; therefore, temperatures can be used to trace water movement. This chapter focuses on the use of chemical and isotopic tracers in the subsurface to estimate recharge. Tracer use in surface-water studies to determine groundwater discharge to streams is addressed in Chapter 4; the use of temperature as a tracer is described in Chapter 8.Following the nomenclature of Scanlon et al. (2002b), tracers are grouped into three categories: natural environmental tracers, historical tracers, and applied tracers. Natural environmental tracers are those that are transported to or created within the atmosphere under natural processes; these tracers are carried to the Earth’s surface as wet or dry atmospheric deposition. The most commonly used natural environmental tracer is chloride (Cl) (Allison and Hughes, 1978). Ocean water, through the process of evaporation, is the primary source of atmospheric Cl. Other tracers in this category include chlorine-36 (36Cl) and tritium (3H); these two isotopes are produced naturally in the Earth’s atmosphere; however, there are additional anthropogenic sources of them.

  10. The relationship between supplier networks and industrial clusters: an analysis based on the cluster mapping method

    Directory of Open Access Journals (Sweden)

    Ichiro IWASAKI

    2010-06-01

    Full Text Available Michael Porter’s concept of competitive advantages emphasizes the importance of regional cooperation of various actors in order to gain competitiveness on globalized markets. Foreign investors may play an important role in forming such cooperation networks. Their local suppliers tend to concentrate regionally. They can form, together with local institutions of education, research, financial and other services, development agencies, the nucleus of cooperative clusters. This paper deals with the relationship between supplier networks and clusters. Two main issues are discussed in more detail: the interest of multinational companies in entering regional clusters and the spillover effects that may stem from their participation. After the discussion on the theoretical background, the paper introduces a relatively new analytical method: “cluster mapping” - a method that can spot regional hot spots of specific economic activities with cluster building potential. Experience with the method was gathered in the US and in the European Union. After the discussion on the existing empirical evidence, the authors introduce their own cluster mapping results, which they obtained by using a refined version of the original methodology.

  11. An Examination of Three Spatial Event Cluster Detection Methods

    Directory of Open Access Journals (Sweden)

    Hensley H. Mariathas

    2015-03-01

    Full Text Available In spatial disease surveillance, geographic areas with large numbers of disease cases are to be identified, so that targeted investigations can be pursued. Geographic areas with high disease rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. In some situations, disease-related events rather than individuals are of interest for geographical surveillance, and methods to detect clusters of disease-related events are called event cluster detection methods. In this paper, we examine three distributional assumptions for the events in cluster detection: compound Poisson, approximate normal and multiple hypergeometric (exact. The methods differ on the choice of distributional assumption for the potentially multiple correlated events per individual. The methods are illustrated on emergency department (ED presentations by children and youth (age < 18 years because of substance use in the province of Alberta, Canada, during 1 April 2007, to 31 March 2008. Simulation studies are conducted to investigate Type I error and the power of the clustering methods.

  12. Chemical analysis of eight giant stars of the globular cluster NGC 6366

    Science.gov (United States)

    Puls, Arthur A.; Alves-Brito, Alan; Campos, Fabíola; Dias, Bruno; Barbuy, Beatriz

    2018-05-01

    The metal-rich Galactic globular cluster NGC 6366 is the fifth closest to the Sun. Despite its interest, it has received scarce attention, and little is known about its internal structure. Its kinematics suggests a link to the halo, but its metallicity indicates otherwise. We present a detailed chemical analysis of eight giant stars of NGC 6366, using high-resolution and high-quality spectra (R > 40 000, S/N > 60) obtained at the VLT (8.2 m) and CFHT (3.6 m) telescopes. We attempted to characterize its chemistry and to search for evidence of multiple stellar populations. The atmospheric parameters were derived using the method of excitation and ionization equilibrium of Fe I and Fe II lines and from those atmospheric parameters we calculated the abundances for other elements and found that none of the elements measured presents star-to-star variation greater than the uncertainties. We compared the derived abundances with those of other globular clusters and field stars available in the literature. We determined a mean [Fe/H] = -0.60 ± 0.03 for NGC 6366 and found some similarity of this object with M 71, another inner halo globular cluster. The Na-O anticorrelation extension is short and no star-to-star variation in Al is found. The presence of second generation stars is not evident in NGC 6366.

  13. Zintl Clusters as Wet-Chemical Precursors for Germanium Nanomorphologies with Tunable Composition.

    Science.gov (United States)

    Bentlohner, Manuel M; Waibel, Markus; Zeller, Patrick; Sarkar, Kuhu; Müller-Buschbaum, Peter; Fattakhova-Rohlfing, Dina; Fässler, Thomas F

    2016-02-12

    [Ge9](4-) Zintl clusters are used as soluble germanium source for a bottom-up fabrication of Ge nanomorphologies such as inverse opal structures with tunable composition. The method is based on the assembly and oxidation of [Ge9 ](4-) clusters in a template mold using SiCl4 , GeCl4 , and PCl3 leading to Si and P-containing Ge phases as shown by X-ray diffraction, Raman spectroscopy, and energy-dispersive X-ray analysis. [Ge9](4-) clusters are retained using ethylenediamine (en) as a transfer medium to a mold after removal of the solvent if water is thoroughly excluded, but are oxidized to amorphous Ge in presence of water traces. (1)H NMR spectroscopy reveals the oxidative deprotonation of en by [Ge9](4-). Subsequent annealing leads to crystalline Ge. As an example for wet-chemical synthesis of complex Ge nanomorphologies, we describe the fabrication of undoped and P-doped inverse opal-structured Ge films with a rather low oxygen contents. The morphology of the films with regular volume porosity is characterized by SEM, TEM, and grazing incidence small-angle X-ray scattering. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Dynamics, Chemical Abundances, and ages of Globular Clusters in the Virgo Cluster of Galaxies

    Science.gov (United States)

    Guhathakurta, Puragra; NGVS Collaboration

    2018-01-01

    We present a study of the dynamics, metallicities, and ages of globular clusters (GCs) in the Next Generation Virgo cluster Survey (NGVS), a deep, multi-band (u, g, r, i, z, and Ks), wide-field (104 deg2) imaging survey carried out using the 3.6-m Canada-France-Hawaii Telescope and MegaCam imager. GC candidates were selected from the NGVS survey using photometric and image morphology criteria and these were followed up with deep, medium-resolution, multi-object spectroscopy using the Keck II 10-m telescope and DEIMOS spectrograph. The primary spectroscopic targets were candidate GC satellites of dwarf elliptical (dE) and ultra-diffuse galaxies (UDGs) in the Virgo cluster. While many objects were confirmed as GC satellites of Virgo dEs and UDGs, many turned out to be non-satellites based on their radial velocity and/or positional mismatch any identifiable Virgo cluster galaxy. We have used a combination of spectral characteristics (e.g., presence of absorption vs. emission lines), new Gaussian mixture modeling of radial velocity and sky position data, and a new extreme deconvolution analysis of ugrizKs photometry and image morphology, to classify all the objects in our sample into: (1) GC satellites of dE galaxies, (2) GC satellites of UDGs, (3) intra-cluster GCs (ICGCs) in the Virgo cluster, (4) GCs in the outer halo of the central cluster galaxy M87, (5) foreground Milky Way stars, and (6) distant background galaxies. We use these data to study the dynamics and dark matter content of dE and UDGs in the Virgo cluster, place important constraints on the nature of dE nuclei, and study the origin of ICGCs versus GCs in the remote M87 halo.We are grateful for financial support from the NSF and NASA/STScI.

  15. Comparison of Chemical and Physical-chemical Wastewater Discoloring Methods

    Directory of Open Access Journals (Sweden)

    Durašević, V.

    2007-11-01

    Full Text Available Today's chemical and physical-chemical wastewater discoloration methods do not completely meet demands regarding degree of discoloration. In this paper discoloration was performed using Fenton (FeSO4 . 7 H2O + H2O2 + H2SO4 and Fenton-like (FeCl3 . 6 H2O + H2O2 + HCOOH chemical methods and physical-chemical method of coagulation/flocculation (using poly-electrolyte (POEL combining anion active coagulant (modified poly-acrylamides and cationic flocculant (product of nitrogen compounds in combination with adsorption on activated carbon. Suitability of aforementioned methods was investigated on reactive and acid dyes, regarding their most common use in the textile industry. Also, investigations on dyes of different chromogen (anthraquinone, phthalocyanine, azo and xanthene were carried out in order to determine the importance of molecular spatial structure. Oxidative effect of Fenton and Fenton-like reagents resulted in decomposition of colored chromogen and high degree of discoloration. However, the problem is the inability of adding POEL in stechiometrical ratio (also present in physical-chemical methods, when the phenomenon of overdosing coagulants occurs in order to obtain a higher degree of discoloration, creating a potential danger of burdening water with POEL. Input and output water quality was controlled through spectrophotometric measurements and standard biological parameters. In addition, part of the investigations concerned industrial wastewaters obtained from dyeing cotton materials using reactive dye (C. I. Reactive Blue 19, a process that demands the use of vast amounts of electrolytes. Also, investigations of industrial wastewaters was labeled as a crucial step carried out in order to avoid serious misassumptions and false conclusions, which may arise if dyeing processes are only simulated in the laboratory.

  16. Sensitivity evaluation of dynamic speckle activity measurements using clustering methods

    International Nuclear Information System (INIS)

    Etchepareborda, Pablo; Federico, Alejandro; Kaufmann, Guillermo H.

    2010-01-01

    We evaluate and compare the use of competitive neural networks, self-organizing maps, the expectation-maximization algorithm, K-means, and fuzzy C-means techniques as partitional clustering methods, when the sensitivity of the activity measurement of dynamic speckle images needs to be improved. The temporal history of the acquired intensity generated by each pixel is analyzed in a wavelet decomposition framework, and it is shown that the mean energy of its corresponding wavelet coefficients provides a suited feature space for clustering purposes. The sensitivity obtained by using the evaluated clustering techniques is also compared with the well-known methods of Konishi-Fujii, weighted generalized differences, and wavelet entropy. The performance of the partitional clustering approach is evaluated using simulated dynamic speckle patterns and also experimental data.

  17. The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Current Status

    Science.gov (United States)

    Frinchaboy, Peter; O'Connell, Julia; Donor, John; Cunha, Katia; Thompson, Benjamin; Melendez, Matthew; Shetrone, Matthew; Zasowski, Gail; Majewski, Steven R.; APOGEE TEAM

    2018-01-01

    The Open Cluster Chemical Analysis and Mapping (OCCAM) survey aims to produce a comprehensive, uniform, infrared-based data set forhundreds of open clusters, and constrain key Galactic dynamical and chemical parameters using the SDSS/APOGEE survey and follow-up from the McDonald Observatory Otto Struve 2.1-m telescope and Sandiford Cass Echelle Spectrograph (R ~ 60,000). We report on multi-element radial abundance gradients obtained from a sample of over 30 disk open clusters. The APOGEE chemical abundances were derived automatically by the ASPCAP pipeline and these are part of the SDSS IV Data Release 14, optical follow-up were analyzed using equivalent width analysis and spectral synthesis. We present the current open cluster sample that spans a significant range in age allowing exploration of the evolution of the Galactic abundance gradients. This work is supported by an NSF AAG grants AST-1311835 & AST-1715662.

  18. Momentum-space cluster dual-fermion method

    Science.gov (United States)

    Iskakov, Sergei; Terletska, Hanna; Gull, Emanuel

    2018-03-01

    Recent years have seen the development of two types of nonlocal extensions to the single-site dynamical mean field theory. On one hand, cluster approximations, such as the dynamical cluster approximation, recover short-range momentum-dependent correlations nonperturbatively. On the other hand, diagrammatic extensions, such as the dual-fermion theory, recover long-ranged corrections perturbatively. The correct treatment of both strong short-ranged and weak long-ranged correlations within the same framework is therefore expected to lead to a quick convergence of results, and offers the potential of obtaining smooth self-energies in nonperturbative regimes of phase space. In this paper, we present an exact cluster dual-fermion method based on an expansion around the dynamical cluster approximation. Unlike previous formulations, our method does not employ a coarse-graining approximation to the interaction, which we show to be the leading source of error at high temperature, and converges to the exact result independently of the size of the underlying cluster. We illustrate the power of the method with results for the second-order cluster dual-fermion approximation to the single-particle self-energies and double occupancies.

  19. Polarizable Density Embedding Coupled Cluster Method

    DEFF Research Database (Denmark)

    Hršak, Dalibor; Olsen, Jógvan Magnus Haugaard; Kongsted, Jacob

    2018-01-01

    by an embedding potential consisting of a set of fragment densities obtained from calculations on isolated fragments with a quantum-chemistry method such as Hartree-Fock (HF) or Kohn-Sham density functional theory (KS-DFT) and dressed with a set of atom-centered anisotropic dipole-dipole polarizabilities...

  20. Probabilistic vulnerability assessment of chemical clusters subjected to external acts of interference

    NARCIS (Netherlands)

    Argenti, F.; Landucci, G; Reniers, G.L.L.M.E.

    2016-01-01

    Acts of interference against chemical facilities or chemical clusters might result in severe consequences in
    case of a successful attack (major explosions, fires, toxic dispersions or environmental contamination).
    Although process facilities implement multiple safety barriers to control

  1. Cluster analysis to evaluate stable chemical elements and physical-chemical parameters behavior on uranium mining waste

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Wagner de Souza; Py Junior, Delcy de Azevedo; Goncalves, Simone, E-mail: wspereira@inb.gov.br [Unidade de Tratamento de Minerio (UTM/INB), Pocos de Caldas, MG (Brazil). Coordenacao de Protecao Radiologica. Grupo Multidisciplinar de Radioprotecao; Kelecom, Alphonse [Universidade Federal Fluminense (UFF), Niteroi, RJ (Brazil). Inst. de Biologia. Lab. de Radiobiologia e Radiometria Pedro Lopes dos Santos; Morais, Gustavo Ferrari de; Campelo, Emanuele Lazzaretti Cordova [Unidade de Tratamento de Minerio (UTM/INB), Pocos de Caldas, MG (Brazil). Coordenacao de Desenvolvimento de Processos; Dores, Luis Augusto de Carvalho Bresser [Unidade de Tratamento de Minerio (UTM/INB), Pocos de Caldas, MG (Brazil). Gerencia de Descomissionamento

    2011-07-01

    The Ore Treating Unit (UTM, in portuguese) is a deactivated uranium mine. A cluster analysis was used to evaluate the behavior of stable chemical elements and physical-chemical parameters in their effluents. The utilization of the cluster analysis proved itself effective in the assessment, allowing the identification of groups of chemical elements, physical-chemical parameters and their joint analysis (elements and parameters). As a result we may assert, based on data analysis, that there is a strong link between calcium and magnesium and between aluminum and rare-earth oxides on UTM's effluents. Sulphate was also identified as strongly linked to total and dissolved solids, and those to electrical conductivity. There were other associations, but not so strongly linked. Further gathering, to seasonal evaluation, are required in order to confirm those analysis. Additional statistical analysis (factor analysis) must be used to try to identify the origin of the identified groups on this analysis. (author)

  2. Cluster analysis to evaluate stable chemical elements and physical-chemical parameters behavior on uranium mining waste

    International Nuclear Information System (INIS)

    Pereira, Wagner de Souza; Py Junior, Delcy de Azevedo; Goncalves, Simone; Kelecom, Alphonse; Morais, Gustavo Ferrari de; Campelo, Emanuele Lazzaretti Cordova; Dores, Luis Augusto de Carvalho Bresser

    2011-01-01

    The Ore Treating Unit (UTM, in portuguese) is a deactivated uranium mine. A cluster analysis was used to evaluate the behavior of stable chemical elements and physical-chemical parameters in their effluents. The utilization of the cluster analysis proved itself effective in the assessment, allowing the identification of groups of chemical elements, physical-chemical parameters and their joint analysis (elements and parameters). As a result we may assert, based on data analysis, that there is a strong link between calcium and magnesium and between aluminum and rare-earth oxides on UTM's effluents. Sulphate was also identified as strongly linked to total and dissolved solids, and those to electrical conductivity. There were other associations, but not so strongly linked. Further gathering, to seasonal evaluation, are required in order to confirm those analysis. Additional statistical analysis (factor analysis) must be used to try to identify the origin of the identified groups on this analysis. (author)

  3. Method for detecting clusters of possible uranium deposits

    International Nuclear Information System (INIS)

    Conover, W.J.; Bement, T.R.; Iman, R.L.

    1978-01-01

    When a two-dimensional map contains points that appear to be scattered somewhat at random, a question that often arises is whether groups of points that appear to cluster are merely exhibiting ordinary behavior, which one can expect with any random distribution of points, or whether the clusters are too pronounced to be attributable to chance alone. A method for detecting clusters along a straight line is applied to the two-dimensional map of 214 Bi anomalies observed as part of the National Uranium Resource Evaluation Program in the Lubbock, Texas, region. Some exact probabilities associated with this method are computed and compared with two approximate methods. The two methods for approximating probabilities work well in the cases examined and can be used when it is not feasible to obtain the exact probabilities

  4. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  5. Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

    Science.gov (United States)

    Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

    2016-01-01

    Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

  6. A novel clustering and supervising users' profiles method

    Institute of Scientific and Technical Information of China (English)

    Zhu Mingfu; Zhang Hongbin; Song Fangyun

    2005-01-01

    To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.

  7. An efficient laser vaporization source for chemically modified metal clusters characterized by thermodynamics and kinetics

    Science.gov (United States)

    Masubuchi, Tsugunosuke; Eckhard, Jan F.; Lange, Kathrin; Visser, Bradley; Tschurl, Martin; Heiz, Ulrich

    2018-02-01

    A laser vaporization cluster source that has a room for cluster aggregation and a reactor volume, each equipped with a pulsed valve, is presented for the efficient gas-phase production of chemically modified metal clusters. The performance of the cluster source is evaluated through the production of Ta and Ta oxide cluster cations, TaxOy+ (y ≥ 0). It is demonstrated that the cluster source produces TaxOy+ over a wide mass range, the metal-to-oxygen ratio of which can easily be controlled by changing the pulse duration that influences the amount of reactant O2 introduced into the cluster source. Reaction kinetic modeling shows that the generation of the oxides takes place under thermalized conditions at less than 300 K, whereas metal cluster cores are presumably created with excess heat. These characteristics are also advantageous to yield "reaction intermediates" of interest via reactions between clusters and reactive molecules in the cluster source, which may subsequently be mass selected for their reactivity measurements.

  8. Spectroscopic Chemical Analysis Methods and Apparatus

    Science.gov (United States)

    Hug, William F. (Inventor); Reid, Ray D. (Inventor); Bhartia, Rohit (Inventor); Lane, Arthur L. (Inventor)

    2018-01-01

    Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted along with photoluminescence spectroscopy (i.e. fluorescence and/or phosphorescence spectroscopy) to provide high levels of sensitivity and specificity in the same instrument.

  9. Cluster electric spectroscopy of colloid chemical oxyhydrate systems

    CERN Document Server

    Sucharev, Yu I

    2015-01-01

    This monograph deals with the shape of Liesegang operator and its respective phase diagrams of spontaneous surges and analyzed properties of cluster attractors. It describes the influence of pulsation noise or self-organization current of gel systems in a magnetic field on singularities of optic parameters of yttrium oxyhydrate, as well as on kinetic curves of changes in optic density of oxyhydrate systems, sorptive properties of d- and f-elements, and the structural organization of their colloids. This monograph is meant for postgraduate students, magisters, researchers, and those interested

  10. VBSCF Methods: Classical Chemical Concepts and Beyond

    NARCIS (Netherlands)

    Rashid, Z.

    2013-01-01

    The aim of this research has been to extend the ab initio Valence Bond Self-Consistent Field (VBSCF) methodology and to apply this method to the electronic structure of molecules. The valence bond method directly deals with the chemical structure of molecules in a pictorial language, which chemists

  11. Image Registration Using Single Cluster PHD Methods

    Science.gov (United States)

    Campbell, M.; Schlangen, I.; Delande, E.; Clark, D.

    Cadets in the Department of Physics at the United States Air Force Academy are using the technique of slitless spectroscopy to analyze the spectra from geostationary satellites during glint season. The equinox periods of the year are particularly favorable for earth-based observers to detect specular reflections off satellites (glints), which have been observed in the past using broadband photometry techniques. Three seasons of glints were observed and analyzed for multiple satellites, as measured across the visible spectrum using a diffraction grating on the Academy’s 16-inch, f/8.2 telescope. It is clear from the results that the glint maximum wavelength decreases relative to the time periods before and after the glint, and that the spectral reflectance during the glint is less like a blackbody. These results are consistent with the presumption that solar panels are the predominant source of specular reflection. The glint spectra are also quantitatively compared to different blackbody curves and the solar spectrum by means of absolute differences and standard deviations. Our initial analysis appears to indicate a potential method of determining relative power capacity.

  12. Vinayaka : A Semi-Supervised Projected Clustering Method Using Differential Evolution

    OpenAIRE

    Satish Gajawada; Durga Toshniwal

    2012-01-01

    Differential Evolution (DE) is an algorithm for evolutionary optimization. Clustering problems have beensolved by using DE based clustering methods but these methods may fail to find clusters hidden insubspaces of high dimensional datasets. Subspace and projected clustering methods have been proposed inliterature to find subspace clusters that are present in subspaces of dataset. In this paper we proposeVINAYAKA, a semi-supervised projected clustering method based on DE. In this method DE opt...

  13. Kernel method for clustering based on optimal target vector

    International Nuclear Information System (INIS)

    Angelini, Leonardo; Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2006-01-01

    We introduce Ising models, suitable for dichotomic clustering, with couplings that are (i) both ferro- and anti-ferromagnetic (ii) depending on the whole data-set and not only on pairs of samples. Couplings are determined exploiting the notion of optimal target vector, here introduced, a link between kernel supervised and unsupervised learning. The effectiveness of the method is shown in the case of the well-known iris data-set and in benchmarks of gene expression levels, where it works better than existing methods for dichotomic clustering

  14. Agent-based method for distributed clustering of textual information

    Science.gov (United States)

    Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

    2010-09-28

    A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

  15. A cluster-based strategy for assessing the overlap between large chemical libraries and its application to a recent acquisition.

    Science.gov (United States)

    Engels, Michael F M; Gibbs, Alan C; Jaeger, Edward P; Verbinnen, Danny; Lobanov, Victor S; Agrafiotis, Dimitris K

    2006-01-01

    We report on the structural comparison of the corporate collections of Johnson & Johnson Pharmaceutical Research & Development (JNJPRD) and 3-Dimensional Pharmaceuticals (3DP), performed in the context of the recent acquisition of 3DP by JNJPRD. The main objective of the study was to assess the druglikeness of the 3DP library and the extent to which it enriched the chemical diversity of the JNJPRD corporate collection. The two databases, at the time of acquisition, collectively contained more than 1.1 million compounds with a clearly defined structural description. The analysis was based on a clustering approach and aimed at providing an intuitive quantitative estimate and visual representation of this enrichment. A novel hierarchical clustering algorithm called divisive k-means was employed in combination with Kelley's cluster-level selection method to partition the combined data set into clusters, and the diversity contribution of each library was evaluated as a function of the relative occupancy of these clusters. Typical 3DP chemotypes enriching the diversity of the JNJPRD collection were catalogued and visualized using a modified maximum common substructure algorithm. The joint collection of JNJPRD and 3DP compounds was also compared to other databases of known medicinally active or druglike compounds. The potential of the methodology for the analysis of very large chemical databases is discussed.

  16. The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Optical Extension for Neutron Capture Elements

    Science.gov (United States)

    Melendez, Matthew; O'Connell, Julia; Frinchaboy, Peter M.; Donor, John; Cunha, Katia M. L.; Shetrone, Matthew D.; Majewski, Steven R.; Zasowski, Gail; Pinsonneault, Marc H.; Roman-Lopes, Alexandre; Stassun, Keivan G.; APOGEE Team

    2017-01-01

    The Open Cluster Chemical Abundance & Mapping (OCCAM) survey is a systematic survey of Galactic open clusters using data primarily from the SDSS-III/APOGEE-1 survey. However, neutron capture elements are very limited in the IR region covered by APOGEE. In an effort to fully study detailed Galactic chemical evolution, we are conducting a high resolution (R~60,000) spectroscopic abundance analysis of neutron capture elements for OCCAM clusters in the optical regime to complement the APOGEE results. As part of this effort, we present Ba II, La II, Ce II and Eu II results for a few open clusters without previous abundance measurements using data obtained at McDonald Observatory with the 2.1m Otto Struve telescope and Sandiford Echelle Spectrograph.This work is supported by an NSF AAG grant AST-1311835.

  17. A cluster approximation for the transfer-matrix method

    International Nuclear Information System (INIS)

    Surda, A.

    1990-08-01

    A cluster approximation for the transfer-method is formulated. The calculation of the partition function of lattice models is transformed to a nonlinear mapping problem. The method yields the free energy, correlation functions and the phase diagrams for a large class of lattice models. The high accuracy of the method is exemplified by the calculation of the critical temperature of the Ising model. (author). 14 refs, 2 figs, 1 tab

  18. Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

    Energy Technology Data Exchange (ETDEWEB)

    Boukherroub, R.; Wayner, D.D.M. [Steacie Institute for Molecular Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Lockwood, D.J. [Institute for Microstructural Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Zargarian, D. [Chemistry Department, University of Montreal, C.P. 6128, succursale, Centre-ville, Montreal QC (Canada)

    2003-05-01

    This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group. (Abstract Copyright [2003], Wiley Periodicals, Inc.)

  19. Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

    Science.gov (United States)

    Boukherroub, R.; Wayner, D. D. M.; Lockwood, D. J.; Zargarian, D.

    2003-05-01

    This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group.

  20. Chemical decontaminating method for stainless steel

    International Nuclear Information System (INIS)

    Onuma, Tsutomu; Akimoto, Hidetoshi.

    1990-01-01

    Radioactive metal wastes comprising passivated stainless steels are chemically decontaminated to such a radioactivity level as that of usual wastes. The present invention for chemically decontaminating stainless steels comprises a first step of immersing decontaminates into a sulfuric acid solution and a second step of immersing them into an aqueous solution prepared by adding oxidative metal salts to sulfuric acid, in which a portion of the surface of stainless steels as decontaminates are chemically ground to partially expose substrate materials and then the above-mentioned decontamination steps are applied. More than 90% of radioactive materials are removed in this method by the dissolution of the exposed substrate materials and peeling of cruds secured to the surface of the materials upon dissolution. This method is applicable to decontamination of articles having complicate shapes, can reduce the amount of secondary wastes after decontamination and also remarkably shorten the time required for decontamination. (T.M.)

  1. Fuzzy Clustering Methods and their Application to Fuzzy Modeling

    DEFF Research Database (Denmark)

    Kroszynski, Uri; Zhou, Jianjun

    1999-01-01

    Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate....... An illustrative synthetic example is analyzed, and prediction accuracy measures are compared between the different variants...

  2. Dynamic analysis of clustered building structures using substructures methods

    International Nuclear Information System (INIS)

    Leimbach, K.R.; Krutzik, N.J.

    1989-01-01

    The dynamic substructure approach to the building cluster on a common base mat starts with the generation of Ritz-vectors for each building on a rigid foundation. The base mat plus the foundation soil is subjected to kinematic constraint modes, for example constant, linear, quadratic or cubic constraints. These constraint modes are also imposed on the buildings. By enforcing kinematic compatibility of the complete structural system on the basis of the constraint modes a reduced Ritz model of the complete cluster is obtained. This reduced model can now be analyzed by modal time history or response spectrum methods

  3. Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

    2015-10-01

    Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

  4. Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

    Science.gov (United States)

    Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

    2016-01-01

    Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

  5. a Probabilistic Embedding Clustering Method for Urban Structure Detection

    Science.gov (United States)

    Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

    2017-09-01

    Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

  6. A PROBABILISTIC EMBEDDING CLUSTERING METHOD FOR URBAN STRUCTURE DETECTION

    Directory of Open Access Journals (Sweden)

    X. Lin

    2017-09-01

    Full Text Available Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM to find latent features from high dimensional urban sensing data by “learning” via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

  7. Application of a Light-Front Coupled Cluster Method

    International Nuclear Information System (INIS)

    Chabysheva, S.S.; Hiller, J.R.

    2012-01-01

    As a test of the new light-front coupled-cluster method in a gauge theory, we apply it to the nonperturbative construction of the dressed-electron state in QED, for an arbitrary covariant gauge, and compute the electron's anomalous magnetic moment. The construction illustrates the spectator and Fock-sector independence of vertex and self-energy contributions and indicates resolution of the difficulties with uncanceled divergences that plague methods based on Fock-space truncation. (author)

  8. A Clustering Method for Data in Cylindrical Coordinates

    Directory of Open Access Journals (Sweden)

    Kazuhisa Fujita

    2017-01-01

    Full Text Available We propose a new clustering method for data in cylindrical coordinates based on the k-means. The goal of the k-means family is to maximize an optimization function, which requires a similarity. Thus, we need a new similarity to obtain the new clustering method for data in cylindrical coordinates. In this study, we first derive a new similarity for the new clustering method by assuming a particular probabilistic model. A data point in cylindrical coordinates has radius, azimuth, and height. We assume that the azimuth is sampled from a von Mises distribution and the radius and the height are independently generated from isotropic Gaussian distributions. We derive the new similarity from the log likelihood of the assumed probability distribution. Our experiments demonstrate that the proposed method using the new similarity can appropriately partition synthetic data defined in cylindrical coordinates. Furthermore, we apply the proposed method to color image quantization and show that the methods successfully quantize a color image with respect to the hue element.

  9. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Ryan B., E-mail: randerson@astro.cornell.edu [Cornell University Department of Astronomy, 406 Space Sciences Building, Ithaca, NY 14853 (United States); Bell, James F., E-mail: Jim.Bell@asu.edu [Arizona State University School of Earth and Space Exploration, Bldg.: INTDS-A, Room: 115B, Box 871404, Tempe, AZ 85287 (United States); Wiens, Roger C., E-mail: rwiens@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States); Morris, Richard V., E-mail: richard.v.morris@nasa.gov [NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX 77058 (United States); Clegg, Samuel M., E-mail: sclegg@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States)

    2012-04-15

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO{sub 2} at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by {approx} 3 wt.%. The statistical significance of these improvements was {approx} 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and

  10. A method of clustering observers with different visual characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Niimi, Takanaga [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Imai, Kuniharu [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Ikeda, Mitsuru [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan); Maeda, Hisatoshi [Nagoya University School of Health Sciences, Department of Radiological Technology, 1-1-20 Daiko-minami, Higashi-ku, Nagoya 461-8673 (Japan)

    2006-01-15

    Evaluation of observer's image perception in medical images is important, and yet has not been performed because it is difficult to quantify visual characteristics. In the present study, we investigated the observer's image perception by clustering a group of 20 observers. Images of a contrast-detail (C-D) phantom, which had cylinders of 10 rows and 10 columns with different diameters and lengths, were acquired with an X-ray screen-film system with fixed exposure conditions. A group of 10 films were prepared for visual evaluations. Sixteen radiological technicians, three radiologists and one medical physicist participated in the observation test. All observers read the phantom radiographs on a transillumination image viewer with room lights off. The detectability was defined as the shortest length of the cylinders of which border the observers could recognize from the background, and was recorded using the number of columns. The detectability was calculated as the average of 10 readings for each observer, and plotted for different phantom diameter. The unweighted pair-group method using arithmetic averages (UPGMA) was adopted for clustering. The observers were clustered into two groups: one group selected objects with a demarcation from the vicinity, and the other group searched for the objects with their eyes constrained. This study showed a usefulness of the cluster method to select personnel with the similar perceptual predisposition when a C-D phantom was used in image quality control.

  11. A method of clustering observers with different visual characteristics

    International Nuclear Information System (INIS)

    Niimi, Takanaga; Imai, Kuniharu; Ikeda, Mitsuru; Maeda, Hisatoshi

    2006-01-01

    Evaluation of observer's image perception in medical images is important, and yet has not been performed because it is difficult to quantify visual characteristics. In the present study, we investigated the observer's image perception by clustering a group of 20 observers. Images of a contrast-detail (C-D) phantom, which had cylinders of 10 rows and 10 columns with different diameters and lengths, were acquired with an X-ray screen-film system with fixed exposure conditions. A group of 10 films were prepared for visual evaluations. Sixteen radiological technicians, three radiologists and one medical physicist participated in the observation test. All observers read the phantom radiographs on a transillumination image viewer with room lights off. The detectability was defined as the shortest length of the cylinders of which border the observers could recognize from the background, and was recorded using the number of columns. The detectability was calculated as the average of 10 readings for each observer, and plotted for different phantom diameter. The unweighted pair-group method using arithmetic averages (UPGMA) was adopted for clustering. The observers were clustered into two groups: one group selected objects with a demarcation from the vicinity, and the other group searched for the objects with their eyes constrained. This study showed a usefulness of the cluster method to select personnel with the similar perceptual predisposition when a C-D phantom was used in image quality control

  12. Tracing the Chemical Evolution of Metal-rich Galactic Bulge Globular Clusters

    Science.gov (United States)

    Munoz Gonzalez, Cesar; Saviane, Ivo; Geisler, Doug; Villanova, Sandro

    2018-01-01

    We present in this poster the metallicity characterization of the four metal rich Bulge Galactic Gobular Clusters, which have controversial metallicities. We analyzed our high-resolution spectra (using UVES-580nm and GIRAFFE-HR13 setups) for a large sample of RGB/AGB targets in each cluster in order to measure their metallicity and prove or discard the iron spread hypothesis. We have also characterized chemically stars with potentially different iron content by measuring light (O, Na, Mg, Al), alpha (Si, Ca, Ti), iron–peak (V, Cr, Ni, Mn) and s and r process (Y, Zr, Ba, Eu) elements. We have identified possible channels responsible for the chemical heterogeneity of the cluster populations, like AGB or massive fast-rotating stars contamination, or SN explosion. Also, we have analyzed the origin and evolution of these bulge GCs and their connection with the bulge itself.

  13. Detecting and extracting clusters in atom probe data: A simple, automated method using Voronoi cells

    International Nuclear Information System (INIS)

    Felfer, P.; Ceguerra, A.V.; Ringer, S.P.; Cairney, J.M.

    2015-01-01

    The analysis of the formation of clusters in solid solutions is one of the most common uses of atom probe tomography. Here, we present a method where we use the Voronoi tessellation of the solute atoms and its geometric dual, the Delaunay triangulation to test for spatial/chemical randomness of the solid solution as well as extracting the clusters themselves. We show how the parameters necessary for cluster extraction can be determined automatically, i.e. without user interaction, making it an ideal tool for the screening of datasets and the pre-filtering of structures for other spatial analysis techniques. Since the Voronoi volumes are closely related to atomic concentrations, the parameters resulting from this analysis can also be used for other concentration based methods such as iso-surfaces. - Highlights: • Cluster analysis of atom probe data can be significantly simplified by using the Voronoi cell volumes of the atomic distribution. • Concentration fields are defined on a single atomic basis using Voronoi cells. • All parameters for the analysis are determined by optimizing the separation probability of bulk atoms vs clustered atoms

  14. Unbiased methods for removing systematics from galaxy clustering measurements

    Science.gov (United States)

    Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.

    2016-02-01

    Measuring the angular clustering of galaxies as a function of redshift is a powerful method for extracting information from the three-dimensional galaxy distribution. The precision of such measurements will dramatically increase with ongoing and future wide-field galaxy surveys. However, these are also increasingly sensitive to observational and astrophysical contaminants. Here, we study the statistical properties of three methods proposed for controlling such systematics - template subtraction, basic mode projection, and extended mode projection - all of which make use of externally supplied template maps, designed to characterize and capture the spatial variations of potential systematic effects. Based on a detailed mathematical analysis, and in agreement with simulations, we find that the template subtraction method in its original formulation returns biased estimates of the galaxy angular clustering. We derive closed-form expressions that should be used to correct results for this shortcoming. Turning to the basic mode projection algorithm, we prove it to be free of any bias, whereas we conclude that results computed with extended mode projection are biased. Within a simplified setup, we derive analytical expressions for the bias and discuss the options for correcting it in more realistic configurations. Common to all three methods is an increased estimator variance induced by the cleaning process, albeit at different levels. These results enable unbiased high-precision clustering measurements in the presence of spatially varying systematics, an essential step towards realizing the full potential of current and planned galaxy surveys.

  15. Advanced cluster methods for correlated-electron systems

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Andre

    2015-04-27

    In this thesis, quantum cluster methods are used to calculate electronic properties of correlated-electron systems. A special focus lies in the determination of the ground state properties of a 3/4 filled triangular lattice within the one-band Hubbard model. At this filling, the electronic density of states exhibits a so-called van Hove singularity and the Fermi surface becomes perfectly nested, causing an instability towards a variety of spin-density-wave (SDW) and superconducting states. While chiral d+id-wave superconductivity has been proposed as the ground state in the weak coupling limit, the situation towards strong interactions is unclear. Additionally, quantum cluster methods are used here to investigate the interplay of Coulomb interactions and symmetry-breaking mechanisms within the nematic phase of iron-pnictide superconductors. The transition from a tetragonal to an orthorhombic phase is accompanied by a significant change in electronic properties, while long-range magnetic order is not established yet. The driving force of this transition may not only be phonons but also magnetic or orbital fluctuations. The signatures of these scenarios are studied with quantum cluster methods to identify the most important effects. Here, cluster perturbation theory (CPT) and its variational extention, the variational cluster approach (VCA) are used to treat the respective systems on a level beyond mean-field theory. Short-range correlations are incorporated numerically exactly by exact diagonalization (ED). In the VCA, long-range interactions are included by variational optimization of a fictitious symmetry-breaking field based on a self-energy functional approach. Due to limitations of ED, cluster sizes are limited to a small number of degrees of freedom. For the 3/4 filled triangular lattice, the VCA is performed for different cluster symmetries. A strong symmetry dependence and finite-size effects make a comparison of the results from different clusters difficult

  16. A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method

    Directory of Open Access Journals (Sweden)

    Xiangbing Zhou

    2018-04-01

    Full Text Available Rapidly growing GPS (Global Positioning System trajectories hide much valuable information, such as city road planning, urban travel demand, and population migration. In order to mine the hidden information and to capture better clustering results, a trajectory regression clustering method (an unsupervised trajectory clustering method is proposed to reduce local information loss of the trajectory and to avoid getting stuck in the local optimum. Using this method, we first define our new concept of trajectory clustering and construct a novel partitioning (angle-based partitioning method of line segments; second, the Lagrange-based method and Hausdorff-based K-means++ are integrated in fuzzy C-means (FCM clustering, which are used to maintain the stability and the robustness of the clustering process; finally, least squares regression model is employed to achieve regression clustering of the trajectory. In our experiment, the performance and effectiveness of our method is validated against real-world taxi GPS data. When comparing our clustering algorithm with the partition-based clustering algorithms (K-means, K-median, and FCM, our experimental results demonstrate that the presented method is more effective and generates a more reasonable trajectory.

  17. A sequential-move game for enhancing safety and security cooperation within chemical clusters

    International Nuclear Information System (INIS)

    Pavlova, Yulia; Reniers, Genserik

    2011-01-01

    The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided.

  18. A sequential-move game for enhancing safety and security cooperation within chemical clusters.

    Science.gov (United States)

    Pavlova, Yulia; Reniers, Genserik

    2011-02-15

    The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided. Copyright © 2010 Elsevier B.V. All rights reserved.

  19. Effect of ruthenium cluster on the photoluminescence of chemically derivatized porous silicon

    International Nuclear Information System (INIS)

    Boukherroub, Rabah; Zargarian, Davit; Reber, Christian; Lockwood, David J.; Carty, Arthur J.; Wayner, Danial D.M.

    2003-01-01

    A green photoluminescent triruthenium cluster (I) has been chemisorbed on highly luminescent porous silicon (PSi) layers, either freshly prepared or chemically modified with 1-decene, ethyl undecylenate, or undecylenic acid, in order to study the influence of the cluster on the photoluminescence (PL) arising from the PSi. Immersing the hydrogen-terminated PSi in a hexane solution of (I) for several days at room temperature led to the quenching of PL arising from PSi; the only PL detected was due to the Ru cluster (I). A complete quenching of the PL due to PSi was also observed when derivatized PSi surfaces were exposed to the same solution of (I); in these cases, the PL of (I) also shifted to lower energies. Both the quenching of the PL arising from the PSi layers and the shift in the PL of the cluster (I) are likely due to the difference in the chemical interaction of the PO moiety and the CO groups of the Ru cluster with the terminal functional group of the organic monolayer

  20. Effect of ruthenium cluster on the photoluminescence of chemically derivatized porous silicon

    Energy Technology Data Exchange (ETDEWEB)

    Boukherroub, Rabah; Zargarian, Davit; Reber, Christian; Lockwood, David J.; Carty, Arthur J.; Wayner, Danial D.M

    2003-07-15

    A green photoluminescent triruthenium cluster (I) has been chemisorbed on highly luminescent porous silicon (PSi) layers, either freshly prepared or chemically modified with 1-decene, ethyl undecylenate, or undecylenic acid, in order to study the influence of the cluster on the photoluminescence (PL) arising from the PSi. Immersing the hydrogen-terminated PSi in a hexane solution of (I) for several days at room temperature led to the quenching of PL arising from PSi; the only PL detected was due to the Ru cluster (I). A complete quenching of the PL due to PSi was also observed when derivatized PSi surfaces were exposed to the same solution of (I); in these cases, the PL of (I) also shifted to lower energies. Both the quenching of the PL arising from the PSi layers and the shift in the PL of the cluster (I) are likely due to the difference in the chemical interaction of the PO moiety and the CO groups of the Ru cluster with the terminal functional group of the organic monolayer.

  1. Effect of ruthenium cluster on the photoluminescence of chemically derivatized porous silicon

    Science.gov (United States)

    Boukherroub, Rabah; Zargarian, Davit; Reber, Christian; Lockwood, David J.; Carty, Arthur J.; Wayner, Danial D. M.

    2003-07-01

    A green photoluminescent triruthenium cluster (I) has been chemisorbed on highly luminescent porous silicon (PSi) layers, either freshly prepared or chemically modified with 1-decene, ethyl undecylenate, or undecylenic acid, in order to study the influence of the cluster on the photoluminescence (PL) arising from the PSi. Immersing the hydrogen-terminated PSi in a hexane solution of (I) for several days at room temperature led to the quenching of PL arising from PSi; the only PL detected was due to the Ru cluster (I). A complete quenching of the PL due to PSi was also observed when derivatized PSi surfaces were exposed to the same solution of (I); in these cases, the PL of (I) also shifted to lower energies. Both the quenching of the PL arising from the PSi layers and the shift in the PL of the cluster (I) are likely due to the difference in the chemical interaction of the PO moiety and the CO groups of the Ru cluster with the terminal functional group of the organic monolayer.

  2. Chemically reducing decontamination method for radioactive metal

    International Nuclear Information System (INIS)

    Tanaka, Akio; Onuma, Tsutomu; Sato, Hitoshi.

    1994-01-01

    The present invention concerns a decontamination method of electrolytically reducing radioactive metal wastes, then chemically dissolving the surface thereof with a strong acid decontaminating solution. This method utilizes dissolving characteristics of stainless steels in the strong acid solution. That is, in the electrolytic reduction operation, a portion of the metal wastes is brought into contact with a strong acid decontaminating solution, and voltage and current are applied to the portion and keep it for a long period of time so as to make the potential of the immersed portion of the metal wastes to an active soluble region. Then, the electrolytic reduction operation is stopped, and the metal wastes are entirely immersed in the decontaminating solution to decontaminate by chemical dissolution. As the decontaminating solution, strong acid such as sulfuric acid, nitric acid is used. Since DC current power source capacity required for causing reaction in the active soluble region can be decreased, the decontamination facility can be minimized and simplified, and necessary electric power can be saved even upon decontamination of radioactive metal wastes made of stainless steels and having a great area. Further, chemical dissolution can be conducted without adding an expensive oxidizing agent. (N.H.)

  3. Chemical study of the metal-rich globular cluster NGC 5927

    Science.gov (United States)

    Mura-Guzmán, A.; Villanova, S.; Muñoz, C.; Tang, B.

    2018-03-01

    Globular clusters (GCs) are natural laboratories where stellar and chemical evolution can be studied in detail. In addition, their chemical patterns and kinematics can tell us to which Galactic structure (disc, bulge, halo or extragalactic) the cluster belongs to. NGC 5927 is one of most metal-rich GCs in the Galaxy and its kinematics links it to the thick disc. We present abundance analysis based on high-resolution spectra of seven giant stars. The data were obtained using Fibre Large Array Multi Element Spectrograph/Ultraviolet Echelle Spectrograph (UVES) spectrograph mounted on UT2 telescope of the European Southern Observatory. The principal objective of this work is to perform a wide and detailed chemical abundance analysis of the cluster and look for possible Multiple Populations (MPs). We determined stellar parameters and measured 22 elements corresponding to light (Na, Al), alpha (O, Mg, Si, Ca, Ti), iron-peak (Sc, V, Cr, Mn, Fe, Co, Ni, Cu, Zn), and heavy elements (Y, Zr, Ba, Ce, Nd, Eu). We found a mean iron content of [Fe/H] = -0.47 ± 0.02 (error on the mean). We confirm the existence of MPs in this GC with an O-Na anti-correlation, and moderate spread in Al abundances. We estimate a mean [α/Fe] = 0.25 ± 0.08. Iron-peak elements show no significant spread. The [Ba/Eu] ratios indicate a predominant contribution from SNeII for the formation of the cluster.

  4. Chemical analysis by nuclear methods. v. 2

    International Nuclear Information System (INIS)

    Alfassi, Z.B.

    1998-01-01

    'Chemical analysis by Nuclear Methods' is an effort of some renowned authors in field of nuclear chemistry and radiochemistry which is compiled by Alfassi, Z.B. and translated into Farsi version collected in two volumes. The second volume consists of the following chapters: Detecting ion recoil scattering and elastic scattering are dealt in the eleventh chapter, the twelfth chapter is devoted to nuclear reaction analysis using charged particles, X-ray emission is discussed at thirteenth chapter, the fourteenth chapter is about using ion microprobes, X-ray fluorescence analysis is discussed in the fifteenth chapter, alpha, beta and gamma ray scattering in chemical analysis are dealt in chapter sixteen, Moessbauer spectroscopy and positron annihilation are discussed in chapter seventeen and eighteen; The last two chapters are about isotope dilution analysis and radioimmunoassay

  5. Coupling microscopic and mesoscopic scales to simulate chemical equilibrium between a nanometric carbon cluster and detonation products fluid.

    Science.gov (United States)

    Bourasseau, Emeric; Maillet, Jean-Bernard

    2011-04-21

    This paper presents a new method to obtain chemical equilibrium properties of detonation products mixtures including a solid carbon phase. In this work, the solid phase is modelled through a mesoparticle immersed in the fluid, such that the heterogeneous character of the mixture is explicitly taken into account. Inner properties of the clusters are taken from an equation of state obtained in a previous work, and interaction potential between the nanocluster and the fluid particles is derived from all-atoms simulations using the LCBOPII potential (Long range Carbon Bond Order Potential II). It appears that differences in chemical equilibrium results obtained with this method and the "composite ensemble method" (A. Hervouet et al., J. Phys. Chem. B, 2008, 112.), where fluid and solid phases are considered as non-interacting, are not significant, underlining the fact that considering the inhomogeneity of such system is crucial.

  6. A Comparison of Methods for Player Clustering via Behavioral Telemetry

    DEFF Research Database (Denmark)

    Drachen, Anders; Thurau, C.; Sifa, R.

    2013-01-01

    patterns in the behavioral data, and developing profiles that are actionable to game developers. There are numerous methods for unsupervised clustering of user behavior, e.g. k-means/c-means, Nonnegative Matrix Factorization, or Principal Component Analysis. Although all yield behavior categorizations......, interpretation of the resulting categories in terms of actual play behavior can be difficult if not impossible. In this paper, a range of unsupervised techniques are applied together with Archetypal Analysis to develop behavioral clusters from playtime data of 70,014 World of Warcraft players, covering a five......The analysis of user behavior in digital games has been aided by the introduction of user telemetry in game development, which provides unprecedented access to quantitative data on user behavior from the installed game clients of the entire population of players. Player behavior telemetry datasets...

  7. Genetic k-means clustering approach for mapping human vulnerability to chemical hazards in the industrialized city: a case study of Shanghai, China.

    Science.gov (United States)

    Shi, Weifang; Zeng, Weihua

    2013-06-20

    Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster.

  8. Genetic k-Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China

    Directory of Open Access Journals (Sweden)

    Weihua Zeng

    2013-06-01

    Full Text Available Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster.

  9. Understanding Boron through Size-Selected Clusters: Structure, Chemical Bonding, and Fluxionality

    Energy Technology Data Exchange (ETDEWEB)

    Sergeeva, Alina P.; Popov, Ivan A.; Piazza, Zachary A.; Li, Wei-Li; Romanescu, Constantin; Wang, Lai S.; Boldyrev, Alexander I.

    2014-04-15

    Conspectus Boron is an interesting element with unusual polymorphism. While three-dimensional (3D) structural motifs are prevalent in bulk boron, atomic boron clusters are found to have planar or quasi-planar structures, stabilized by localized two-center–two-electron (2c–2e) σ bonds on the periphery and delocalized multicenter–two-electron (nc–2e) bonds in both σ and π frameworks. Electron delocalization is a result of boron’s electron deficiency and leads to fluxional behavior, which has been observed in B13+ and B19–. A unique capability of the in-plane rotation of the inner atoms against the periphery of the cluster in a chosen direction by employing circularly polarized infrared radiation has been suggested. Such fluxional behaviors in boron clusters are interesting and have been proposed as molecular Wankel motors. The concepts of aromaticity and antiaromaticity have been extended beyond organic chemistry to planar boron clusters. The validity of these concepts in understanding the electronic structures of boron clusters is evident in the striking similarities of the π-systems of planar boron clusters to those of polycyclic aromatic hydrocarbons, such as benzene, naphthalene, coronene, anthracene, or phenanthrene. Chemical bonding models developed for boron clusters not only allowed the rationalization of the stability of boron clusters but also lead to the design of novel metal-centered boron wheels with a record-setting planar coordination number of 10. The unprecedented highly coordinated borometallic molecular wheels provide insights into the interactions between transition metals and boron and expand the frontier of boron chemistry. Another interesting feature discovered through cluster studies is boron transmutation. Even though it is well-known that B–, formed by adding one electron to boron, is isoelectronic to carbon, cluster studies have considerably expanded the possibilities of new structures and new materials using the B

  10. Method of chemical decontamination of stainless steel

    International Nuclear Information System (INIS)

    Onuma, Tsutomu; Akimoto, Hidetoshi.

    1989-01-01

    The present invention concerns a decontamination method of chemically decontaminating radioactive metal wastes of passivated stainless steels to a radioactivity level identical with usual wastes, in which the amount of oxidizable metal salts used is decreased. Metal wastes of stainless steels contaminated at their surface with radioactive materials are immersed in a sulfuric acid solution. In this case, a voltage is applied for a certain period of time so that the potential of the stainless steels comes to an active region. Then, oxidizable metal salt (tetravalent cerium) is added into the sulfuric acid solution. According to this method, since most of radioactive materials are removed in the immersing step to the sulfuric acid solution, the amount of the tetravalent cerium used is as less as 1/700 and the decontamination time is as short as 1/4 as compared with those in the conventional method. (K.M.)

  11. Cluster monte carlo method for nuclear criticality safety calculation

    International Nuclear Information System (INIS)

    Pei Lucheng

    1984-01-01

    One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further

  12. Application of Different Extraction Methods for Investigation of Nonmetallic Inclusions and Clusters in Steels and Alloys

    Directory of Open Access Journals (Sweden)

    Diana Janis

    2014-01-01

    Full Text Available The characterization of nonmetallic inclusions is of importance for the production of clean steel in order to improve the mechanical properties. In this respect, a three-dimensional (3D investigation is considered to be useful for an accurate evaluation of size, number, morphology of inclusions, and elementary distribution in each inclusion particle. In this study, the application of various extraction methods (chemical extraction/etching by acid or halogen-alcohol solutions, electrolysis, sputtering with glow discharge, and so on for 3D estimation of nonmetallic Al2O3 inclusions and clusters in high-alloyed steels was examined and discussed using an Fe-10 mass% Ni alloy and an 18/8 stainless steel deoxidized with Al. Advantages and limitations of different extraction methods for 3D investigations of inclusions and clusters were discussed in comparison to conventional two-dimensional (2D observations on a polished cross section of metal samples.

  13. Neutron-Capture Nucleosynthesis and the Chemical Evolution of Globular Clusters

    Science.gov (United States)

    Shingles, Luke J.

    2015-09-01

    Elements heavier than iron are almost entirely produced in stars through neutron captures and radioactive decays. Of these heavy elements, roughly half are produced by the slow neutron-capture process (s-process), which takes place under extended exposure to low neutron densities. Most of the s-process production occurs in stars with initial masses between roughly 0.8 and 8 solar masses (Msun), which evolve through the Asymptotic Giant Branch (AGB) phase. This thesis explores several topics related to AGB stars and the s-process, with a focus on comparing theoretical models to observations in the literature on planetary nebulae, post-AGB stars, and globular cluster stars. A recurring theme is the uncertainty of carbon-13-pocket formation, which is crucial for building accurate models of s-process nucleosynthesis. We first investigated whether neutron-capture reactions in AGB stars are the cause of the low sulphur abundances in planetary nebulae and post-AGB stars relative to the interstellar medium. Accounting for uncertainties in the size of the partial mixing zone that forms carbon-13 pockets and the rates of neutron-capture and neutron-producing reactions, our models failed to reproduce the observed levels of sulphur destruction. From this, we concluded that AGB nucleosynthesis is not the cause of the sulphur anomaly. We also discovered a new method to constrain the extent of the partial mixing zone using neon abundances in planetary nebulae. We next aimed to discover the stellar sites of the s-process enrichment in globular clusters that have inter- and intra-cluster variation, with the examples of M4 (relative to M5) and M22, respectively. Using a new chemical evolution code developed by the candidate, we tested models with stellar yields from rotating massive stars and AGB stars. We compared our model predictions for the production of s-process elements with abundances from s-poor and s-rich populations. We found that rotating massive stars alone do not

  14. Chemical deposition methods using supercritical fluid solutions

    Science.gov (United States)

    Sievers, Robert E.; Hansen, Brian N.

    1990-01-01

    A method for depositing a film of a desired material on a substrate comprises dissolving at least one reagent in a supercritical fluid comprising at least one solvent. Either the reagent is capable of reacting with or is a precursor of a compound capable of reacting with the solvent to form the desired product, or at least one additional reagent is included in the supercritical solution and is capable of reacting with or is a precursor of a compound capable of reacting with the first reagent or with a compound derived from the first reagent to form the desired material. The supercritical solution is expanded to produce a vapor or aerosol and a chemical reaction is induced in the vapor or aerosol so that a film of the desired material resulting from the chemical reaction is deposited on the substrate surface. In an alternate embodiment, the supercritical solution containing at least one reagent is expanded to produce a vapor or aerosol which is then mixed with a gas containing at least one additional reagent. A chemical reaction is induced in the resulting mixture so that a film of the desired material is deposited.

  15. Radiation-Induced Chemical Dynamics in Ar Clusters Exposed to Strong X-Ray Pulses

    Science.gov (United States)

    Kumagai, Yoshiaki; Jurek, Zoltan; Xu, Weiqing; Fukuzawa, Hironobu; Motomura, Koji; Iablonskyi, Denys; Nagaya, Kiyonobu; Wada, Shin-ichi; Mondal, Subhendu; Tachibana, Tetsuya; Ito, Yuta; Sakai, Tsukasa; Matsunami, Kenji; Nishiyama, Toshiyuki; Umemoto, Takayuki; Nicolas, Christophe; Miron, Catalin; Togashi, Tadashi; Ogawa, Kanade; Owada, Shigeki; Tono, Kensuke; Yabashi, Makina; Son, Sang-Kil; Ziaja, Beata; Santra, Robin; Ueda, Kiyoshi

    2018-06-01

    We show that electron and ion spectroscopy reveals the details of the oligomer formation in Ar clusters exposed to an x-ray free electron laser (XFEL) pulse, i.e., chemical dynamics triggered by x rays. With guidance from a dedicated molecular dynamics simulation tool, we find that van der Waals bonding, the oligomer formation mechanism, and charge transfer among the cluster constituents significantly affect ionization dynamics induced by an XFEL pulse of moderate fluence. Our results clearly demonstrate that XFEL pulses can be used not only to "damage and destroy" molecular assemblies but also to modify and transform their molecular structure. The accuracy of the predictions obtained makes it possible to apply the cluster spectroscopy, in connection with the respective simulations, for estimation of the XFEL pulse fluence in the fluence regime below single-atom multiple-photon absorption, which is hardly accessible with other diagnostic tools.

  16. DETAILED CHEMICAL ABUNDANCES OF FOUR STARS IN THE UNUSUAL GLOBULAR CLUSTER PALOMAR 1

    International Nuclear Information System (INIS)

    Sakari, Charli M.; Venn, Kim A.; Irwin, Mike; Aoki, Wako; Arimoto, Nobuo; Dotter, Aaron

    2011-01-01

    Detailed chemical abundances for 21 elements are presented for four red giants in the anomalous outer halo globular cluster Palomar 1 (R GC = 17.2 kpc, Z = 3.6 kpc) using high-resolution (R = 36, 000) spectra from the High Dispersion Spectrograph on the Subaru Telescope. Pal 1 has long been considered unusual because of its low surface brightness, sparse red giant branch, young age, and its possible association with two extragalactic streams of stars. This paper shows that its chemistry further confirms its unusual nature. The mean metallicity of the four stars, [Fe/H] = -0.60 ± 0.01, is high for a globular cluster so far from the Galactic center, but is low for a typical open cluster. The [α/Fe] ratios, though in agreement with the Galactic stars within the 1σ errors, agree best with the lower values in dwarf galaxies. No signs of the Na/O anticorrelation are detected in Pal 1, though Na appears to be marginally high in all four stars. Pal 1's neutron-capture elements are also unusual: its high [Ba/Y] ratio agrees best with dwarf galaxies, implying an excess of second-peak over first-peak s-process elements, while its [Eu/α] and [Ba/Eu] ratios show that Pal 1's contributions from the r-process must have differed in some way from normal Galactic stars. Therefore, Pal 1 is unusual chemically, as well in its other properties. Pal 1 shares some of its unusual abundance characteristics with the young clusters associated with the Sagittarius dwarf galaxy remnant and the intermediate-age LMC clusters, and could be chemically associated with the Canis Majoris overdensity; however, it does not seem to be similar to the Monoceros/Galactic Anticenter Stellar Stream.

  17. Chemical decontamination method for radioactive metal waste

    International Nuclear Information System (INIS)

    Tanaka, Akio; Onuma, Tsutomu; Yamazaki, Sei; Miura, Haruki.

    1993-01-01

    The present invention provides a chemical decontamination method for radioactive metal wastes, which are generated from radioactive material handling facilities and the surfaces of which are contaminated by radioactive materials. That is, it has a feature of applying acid dissolution simultaneously with mechanical grinding. The radioactive metal wastes are contained in a vessel such as a barrel together with abrasives in a sulfuric acid solution and rotated at several tens rotation per minute. By such procedures for the radioactive metal wastes, (1) cruds and passive membranes are mechanically removed, (2) exposed mother metal materials are uniformly brought into contact with sulfuric acid and further (3) the mother metal materials dissolve the cruds and the passive membranes also chemically by a reducing dissolution (so-called local cell effect). According to the method of the present invention, stainless steel metal wastes having cruds and passive membranes can rapidly and efficiently be decontaminated to a radiation level equal with that of ordinary wastes. (I.S.)

  18. Method of removing crud deposited on fuel element clusters

    International Nuclear Information System (INIS)

    Yokota, Tokunobu; Yashima, Akira; Tajima, Jun-ichiro.

    1982-01-01

    Purpose: To enable easy elimination of claddings deposited on the surface of fuel element. Method: An operator manipulates a pole from above a platform, engages the longitudinal flange of the cover to the opening at the upper end of a channel box and starts up a suction pump. The suction amount of the pump is set such that water flow becomes within the channel box at greater flow rate than the operational flow rate in the channel box of the fuel element clusters during reactor operation. This enables to remove crud deposited on the surface of individual fuel elements with ease and rapidly without detaching the channel box. (Moriyama, K.)

  19. Determining wood chip size: image analysis and clustering methods

    Directory of Open Access Journals (Sweden)

    Paolo Febbi

    2013-09-01

    Full Text Available One of the standard methods for the determination of the size distribution of wood chips is the oscillating screen method (EN 15149- 1:2010. Recent literature demonstrated how image analysis could return highly accurate measure of the dimensions defined for each individual particle, and could promote a new method depending on the geometrical shape to determine the chip size in a more accurate way. A sample of wood chips (8 litres was sieved through horizontally oscillating sieves, using five different screen hole diameters (3.15, 8, 16, 45, 63 mm; the wood chips were sorted in decreasing size classes and the mass of all fractions was used to determine the size distribution of the particles. Since the chip shape and size influence the sieving results, Wang’s theory, which concerns the geometric forms, was considered. A cluster analysis on the shape descriptors (Fourier descriptors and size descriptors (area, perimeter, Feret diameters, eccentricity was applied to observe the chips distribution. The UPGMA algorithm was applied on Euclidean distance. The obtained dendrogram shows a group separation according with the original three sieving fractions. A comparison has been made between the traditional sieve and clustering results. This preliminary result shows how the image analysis-based method has a high potential for the characterization of wood chip size distribution and could be further investigated. Moreover, this method could be implemented in an online detection machine for chips size characterization. An improvement of the results is expected by using supervised multivariate methods that utilize known class memberships. The main objective of the future activities will be to shift the analysis from a 2-dimensional method to a 3- dimensional acquisition process.

  20. The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Galactic Neutron CaptureAbundance Gradients

    Science.gov (United States)

    O'Connell, Julia; Frinchaboy, Peter M.; Shetrone, Matthew D.; Melendez, Matthew; Cunha, Katia; Majewski, Steven R.; Zasowski, Gail; APOGEE Team

    2017-06-01

    The evolution of elements, as a function or age, throughout the Milky Way disk provides a key constraint for galaxy evolution models. In an effort to provide these constraints, we have conducted an investigation into the r- and s- process elemental abundances for a large sample of open clusters as part of an optical follow-up to the SDSS-III/APOGEE-1 survey. Stars were identified as cluster members by the Open Cluster Chemical Abundance & Mapping (OCCAM) survey, which culls member candidates by radial velocity, metallicity and proper motion from the observed APOGEE sample. To obtain data for neutron capture elements in these clusters, we conducted a long-term observing campaign covering three years (2013-2016) using the McDonald Observatory Otto Struve 2.1-m telescope and Sandiford Cass Echelle Spectrograph (R ~ 60,000). We present Galactic neutron capture abundance gradients using 30+ clusters, within 6 kpc of the Sun, covering a range of ages from ~80 Myr to ~10 Gyr .

  1. Chemical Abundances of Red Giant Branch Stars in the Globular Clusters NGC 6333 and NGC 6366

    Science.gov (United States)

    Johnson, Christian I.; Rich, R. M.; Pilachowski, C. A.; Kunder, A. M.

    2013-01-01

    We present chemical abundances and radial velocities for >20 red giant branch (RGB) stars in the Galactic globular clusters NGC 6333 ([Fe/H]≈-1.8) and NGC 6366 ([Fe/H]≈-0.6). The results are based on moderate resolution (R=18,000), high signal-to-noise ratio (>100) spectra obtained with the Hydra multifiber positioner and bench spectrograph on the WIYN 3.5m telescope at Kitt Peak National Observatory. Both objects are likely associated with the Galactic bulge globular cluster system, and we therefore compare the cluster abundance patterns with those of nearby bulge field stars. Additionally, we investigate differences in the O-Na anticorrelation and neutron-capture element dispersion between the two clusters, and compare their abundance patterns with those of similar metallicity halo globular clusters. This material is based upon work supported by the National Science Foundation under award No. AST-1003201 to C.I.J. C.A.P. gratefully acknowledges support from the Daniel Kirkwood Research Fund at Indiana University. R.M.R. acknowledges support from NSF grant AST-0709479 and AST-121120995.

  2. Insight into acid-base nucleation experiments by comparison of the chemical composition of positive, negative, and neutral clusters.

    Science.gov (United States)

    Bianchi, Federico; Praplan, Arnaud P; Sarnela, Nina; Dommen, Josef; Kürten, Andreas; Ortega, Ismael K; Schobesberger, Siegfried; Junninen, Heikki; Simon, Mario; Tröstl, Jasmin; Jokinen, Tuija; Sipilä, Mikko; Adamov, Alexey; Amorim, Antonio; Almeida, Joao; Breitenlechner, Martin; Duplissy, Jonathan; Ehrhart, Sebastian; Flagan, Richard C; Franchin, Alessandro; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Kangasluoma, Juha; Keskinen, Helmi; Kim, Jaeseok; Kirkby, Jasper; Laaksonen, Ari; Lawler, Michael J; Lehtipalo, Katrianne; Leiminger, Markus; Makhmutov, Vladimir; Mathot, Serge; Onnela, Antti; Petäjä, Tuukka; Riccobono, Francesco; Rissanen, Matti P; Rondo, Linda; Tomé, António; Virtanen, Annele; Viisanen, Yrjö; Williamson, Christina; Wimmer, Daniela; Winkler, Paul M; Ye, Penglin; Curtius, Joachim; Kulmala, Markku; Worsnop, Douglas R; Donahue, Neil M; Baltensperger, Urs

    2014-12-02

    We investigated the nucleation of sulfuric acid together with two bases (ammonia and dimethylamine), at the CLOUD chamber at CERN. The chemical composition of positive, negative, and neutral clusters was studied using three Atmospheric Pressure interface-Time Of Flight (APi-TOF) mass spectrometers: two were operated in positive and negative mode to detect the chamber ions, while the third was equipped with a nitrate ion chemical ionization source allowing detection of neutral clusters. Taking into account the possible fragmentation that can happen during the charging of the ions or within the first stage of the mass spectrometer, the cluster formation proceeded via essentially one-to-one acid-base addition for all of the clusters, independent of the type of the base. For the positive clusters, the charge is carried by one excess protonated base, while for the negative clusters it is carried by a deprotonated acid; the same is true for the neutral clusters after these have been ionized. During the experiments involving sulfuric acid and dimethylamine, it was possible to study the appearance time for all the clusters (positive, negative, and neutral). It appeared that, after the formation of the clusters containing three molecules of sulfuric acid, the clusters grow at a similar speed, independent of their charge. The growth rate is then probably limited by the arrival rate of sulfuric acid or cluster-cluster collision.

  3. Using Star Clusters as Tracers of Star Formation and Chemical Evolution: The Chemical Enrichment History of the Large Magellanic Cloud

    Science.gov (United States)

    Chilingarian, Igor V.; Asa’d, Randa

    2018-05-01

    The star formation (SFH) and chemical enrichment (CEH) histories of Local Group galaxies are traditionally studied by analyzing their resolved stellar populations in a form of color–magnitude diagrams obtained with the Hubble Space Telescope. Star clusters can be studied in integrated light using ground-based telescopes to much larger distances. They represent snapshots of the chemical evolution of their host galaxy at different ages. Here we present a simple theoretical framework for the chemical evolution based on the instantaneous recycling approximation (IRA) model. We infer a CEH from an SFH and vice versa using observational data. We also present a more advanced model for the evolution of individual chemical elements that takes into account the contribution of supernovae type Ia. We demonstrate that ages, iron, and α-element abundances of 15 star clusters derived from the fitting of their integrated optical spectra reliably trace the CEH of the Large Magellanic Cloud obtained from resolved stellar populations in the age range 40 Myr age–metallicity relation. Moreover, the present-day total gas mass of the LMC estimated by the IRA model (6.2× {10}8 {M}ȯ ) matches within uncertainties the observed H I mass corrected for the presence of molecular gas (5.8+/- 0.5× {10}8 {M}ȯ ). We briefly discuss how our approach can be used to study SFHs of galaxies as distant as 10 Mpc at the level of detail that is currently available only in a handful of nearby Milky Way satellites. .

  4. Chemical Compounds and Extraction Methods of "Maollahm".

    Science.gov (United States)

    Sadeghpoor, Omid; Dayeni, Manijeh; Razi, Samane

    2016-05-01

    Maollahm or meat juice, a by-product of meat, is a traditional remedy in Persian medicine. This product was used as a nourishment or treatment substance for sick people. According to the ancient Persian medicine, animal meat has more affinity with the human body and the body easily absorbs its nutrition. Therefore, one could resort to maollahm for patients requiring urgent nourishment to boost and strengthen their body. In this work, different ways of preparing maollahm from poultry, goat, cow, and sheep meat are studied. Most of these methods are based on distillation or barbecue before distillation, as prescribed by traditional medicine books. The reactions, chemical processes, and volatile compounds related to different types of cooked meat are also compared with the outcome of recent research studies. The difference between various types of meat is related to their compounds. Different cooking processes such as barbecuing, roasting, cooking, and boiling have an effect on the taste, smell and the chemical constituents of maollahm. Additionally, the type of meat, animal feed, as well as using or removing the fat during the cooking process, have an effect on the produced volatile compounds. Cooking process and the type of meat have a direct effect on the compounds of maollahm. Possible reactions in the preparation process of maollahm are investigated and presented according to the new research studies.

  5. The Detailed Chemical Properties of M31 Star Clusters. I. Fe, Alpha and Light Elements

    Science.gov (United States)

    Colucci, Janet E.; Bernstein, Rebecca A.; Cohen, Judith G.

    2014-12-01

    We present ages, [Fe/H] and abundances of the α elements Ca I, Si I, Ti I, Ti II, and light elements Mg I, Na I, and Al I for 31 globular clusters (GCs) in M31, which were obtained from high-resolution, high signal-to-noise ratio >60 echelle spectra of their integrated light (IL). All abundances and ages are obtained using our original technique for high-resolution IL abundance analysis of GCs. This sample provides a never before seen picture of the chemical history of M31. The GCs are dispersed throughout the inner and outer halo, from 2.5 kpc < R M31 < 117 kpc. We find a range of [Fe/H] within 20 kpc of the center of M31, and a constant [Fe/H] ~ - 1.6 for the outer halo clusters. We find evidence for at least one massive GC in M31 with an age between 1 and 5 Gyr. The α-element ratios are generally similar to the Milky Way GC and field star ratios. We also find chemical evidence for a late-time accretion origin for at least one cluster, which has a different abundance pattern than other clusters at similar metallicity. We find evidence for star-to-star abundance variations in Mg, Na, and Al in the GCs in our sample, and find correlations of Ca, Mg, Na, and possibly Al abundance ratios with cluster luminosity and velocity dispersion, which can potentially be used to constrain GC self-enrichment scenarios. Data presented here were obtained with the HIRES echelle spectrograph on the Keck I telescope. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

  6. THE DETAILED CHEMICAL PROPERTIES OF M31 STAR CLUSTERS. I. Fe, ALPHA AND LIGHT ELEMENTS

    Energy Technology Data Exchange (ETDEWEB)

    Colucci, Janet E.; Bernstein, Rebecca A. [The Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101 (United States); Cohen, Judith G., E-mail: jcolucci@obs.carnegiescience.edu [Palomar Observatory, Mail Stop 105-24, California Institute of Technology, Pasadena, CA 91125 (United States)

    2014-12-20

    We present ages, [Fe/H] and abundances of the α elements Ca I, Si I, Ti I, Ti II, and light elements Mg I, Na I, and Al I for 31 globular clusters (GCs) in M31, which were obtained from high-resolution, high signal-to-noise ratio >60 echelle spectra of their integrated light (IL). All abundances and ages are obtained using our original technique for high-resolution IL abundance analysis of GCs. This sample provides a never before seen picture of the chemical history of M31. The GCs are dispersed throughout the inner and outer halo, from 2.5 kpc < R {sub M31} < 117 kpc. We find a range of [Fe/H] within 20 kpc of the center of M31, and a constant [Fe/H] ∼ – 1.6 for the outer halo clusters. We find evidence for at least one massive GC in M31 with an age between 1 and 5 Gyr. The α-element ratios are generally similar to the Milky Way GC and field star ratios. We also find chemical evidence for a late-time accretion origin for at least one cluster, which has a different abundance pattern than other clusters at similar metallicity. We find evidence for star-to-star abundance variations in Mg, Na, and Al in the GCs in our sample, and find correlations of Ca, Mg, Na, and possibly Al abundance ratios with cluster luminosity and velocity dispersion, which can potentially be used to constrain GC self-enrichment scenarios. Data presented here were obtained with the HIRES echelle spectrograph on the Keck I telescope.

  7. Fast New Method for Temporary Chemical Passivation

    Directory of Open Access Journals (Sweden)

    Marek Solčanský

    2012-12-01

    Full Text Available The main material parameter of silicon, that influences the effectiveness of photovoltaic cells, is the minority carrier bulk lifetime.It may change in the technological process especially during high temperature operations. Monitoring of the carrier bulk-lifetimeis necessary for modifying the whole technological process of production. For the measurement of the minority carrier bulk-lifetimethe characterization method MW PCD (Microwave Photoconductance Decay is used, where the result of measurement is the effectivecarrier lifetime, which is very dependent on the surface recombination velocity and therefore on the quality of a silicon surfacepassivation.This work deals with an examination of a different solution types for the chemical passivation of a silicon surface. Varioussolutions are tested on silicon wafers for their consequent comparison. The main purpose of this work is to find optimal solution, whichsuits the requirements of a time stability and start-up velocity of passivation, reproducibility of the measurements and a possibilityof a perfect cleaning of a passivating solution remains from a silicon surface. Another purpose of this work is to identify the parametersof other quinhydrone solutions with different concentrations as compared with the quinhydrone solution in methanol witha concentration of 0.07 mol/dm³ marked QM007 (referential solution.The method of an effective chemical passivation with a quinhydrone in methanol solution was suggested. The solution witha concentration of 0.07 mol /dm3 fulfills all required criteria. The work also confirms the influence of increased concentrationquinhydrone on the temporal stability of the passivation layer and the effect for textured silicon wafers. In conclusion, the influenceof an illumination and the temperature on the properties of the passivating solution QM007 is discussed.

  8. THE BIZARRE CHEMICAL INVENTORY OF NGC 2419, AN EXTREME OUTER HALO GLOBULAR CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Judith G.; Kirby, Evan N., E-mail: jlc@astro.caltech.edu, E-mail: enk@astro.caltech.edu [Palomar Observatory, Mail Stop 249-17, California Institute of Technology, Pasadena, CA 91125 (United States)

    2012-11-20

    We present new Keck/HIRES observations of six red giants in the globular cluster (GC) NGC 2419. Although the cluster is among the most distant and most luminous in the Milky Way, it was considered chemically ordinary until very recently. Our previous work showed that the near-infrared Ca II triplet line strength varied more than expected for a chemically homogeneous cluster, and that at least one star had unusual abundances of Mg and K. Here, we confirm that NGC 2419 harbors a population of stars, comprising about one-third of its mass, that is depleted in Mg by a factor of eight and enhanced in K by a factor of six with respect to the Mg-normal population. Although the majority, Mg-normal population appears to have a chemical abundance pattern indistinguishable from ordinary, inner-halo GCs, the Mg-poor population exhibits dispersions of several elements. The abundances of K and Sc are strongly anti-correlated with Mg, and some other elements (Si and Ca among others) are weakly anti-correlated with Mg. These abundance patterns suggest that the different populations of NGC 2419 sample the ejecta of diverse supernovae in addition to asymptotic giant branch ejecta. However, the abundances of Fe-peak elements except Sc show no star-to-star variation. We find no nucleosynthetic source that satisfactorily explains all of the abundance variations in this cluster. Because NGC 2419 appears like no other GC, we reiterate our previous suggestion that it is not a GC at all, but rather the core of an accreted dwarf galaxy.

  9. Chemical Methods for Peptide and Protein Production

    Directory of Open Access Journals (Sweden)

    Istvan Toth

    2013-04-01

    Full Text Available Since the invention of solid phase synthetic methods by Merrifield in 1963, the number of research groups focusing on peptide synthesis has grown exponentially. However, the original step-by-step synthesis had limitations: the purity of the final product decreased with the number of coupling steps. After the development of Boc and Fmoc protecting groups, novel amino acid protecting groups and new techniques were introduced to provide high quality and quantity peptide products. Fragment condensation was a popular method for peptide production in the 1980s, but unfortunately the rate of racemization and reaction difficulties proved less than ideal. Kent and co-workers revolutionized peptide coupling by introducing the chemoselective reaction of unprotected peptides, called native chemical ligation. Subsequently, research has focused on the development of novel ligating techniques including the famous click reaction, ligation of peptide hydrazides, and the recently reported a-ketoacid-hydroxylamine ligations with 5-oxaproline. Several companies have been formed all over the world to prepare high quality Good Manufacturing Practice peptide products on a multi-kilogram scale. This review describes the advances in peptide chemistry including the variety of synthetic peptide methods currently available and the broad application of peptides in medicinal chemistry.

  10. Chemical methods for peptide and protein production.

    Science.gov (United States)

    Chandrudu, Saranya; Simerska, Pavla; Toth, Istvan

    2013-04-12

    Since the invention of solid phase synthetic methods by Merrifield in 1963, the number of research groups focusing on peptide synthesis has grown exponentially. However, the original step-by-step synthesis had limitations: the purity of the final product decreased with the number of coupling steps. After the development of Boc and Fmoc protecting groups, novel amino acid protecting groups and new techniques were introduced to provide high quality and quantity peptide products. Fragment condensation was a popular method for peptide production in the 1980s, but unfortunately the rate of racemization and reaction difficulties proved less than ideal. Kent and co-workers revolutionized peptide coupling by introducing the chemoselective reaction of unprotected peptides, called native chemical ligation. Subsequently, research has focused on the development of novel ligating techniques including the famous click reaction, ligation of peptide hydrazides, and the recently reported α-ketoacid-hydroxylamine ligations with 5-oxaproline. Several companies have been formed all over the world to prepare high quality Good Manufacturing Practice peptide products on a multi-kilogram scale. This review describes the advances in peptide chemistry including the variety of synthetic peptide methods currently available and the broad application of peptides in medicinal chemistry.

  11. Chemical decontamination method for radioactive metal waste

    International Nuclear Information System (INIS)

    Onuma, Tsutomu; Akimoto, Hidetoshi

    1991-01-01

    The invention relates to a decontamination method for radioactive metal waste products derived from equipment that handles radioactive materials whose surfaces have been contaminated; in particular it concerns a decontamination method that reduces the amount of radioactive waste by decontaminating radioactive waste substances to a level of radioactivity in line with normal waste products. In order to apply chemical decontamination to metal waste products whose surfaces are divided into carbon steel waste and stainless steel waste; the carbon steel waste is treated using only a primary process in which the waste is immersed in a sulfuric acid solution, while the stainless steel waste must be treated with both the primary process and then electrolytically reduces it for a specific length of time and a secondary process that uses a solution of sulfuric acid mixed with oxidizing metal salts. The method used to categorize metal waste into carbon steel waste and stainless steel waste involves determining the presence, or absence, of magnetism. Voltage is applied for a fixed duration; once that has stopped, electrolytic reduction repeats the operative cycle of applying, then stopping voltage until the potential of the radioactive metal waste is retained in the active region. 1 fig. 2 tabs

  12. Simple method to calculate percolation, Ising and Potts clusters

    International Nuclear Information System (INIS)

    Tsallis, C.

    1981-01-01

    A procedure ('break-collapse method') is introduced which considerably simplifies the calculation of two - or multirooted clusters like those commonly appearing in real space renormalization group (RG) treatments of bond-percolation, and pure and random Ising and Potts problems. The method is illustrated through two applications for the q-state Potts ferromagnet. The first of them concerns a RG calculation of the critical exponent ν for the isotropic square lattice: numerical consistence is obtained (particularly for q→0) with den Nijs conjecture. The second application is a compact reformulation of the standard star-triangle and duality transformations which provide the exact critical temperature for the anisotropic triangular and honeycomb lattices. (Author) [pt

  13. Expanding Comparative Literature into Comparative Sciences Clusters with Neutrosophy and Quad-stage Method

    Directory of Open Access Journals (Sweden)

    Fu Yuhua

    2016-08-01

    Full Text Available By using Neutrosophy and Quad-stage Method, the expansions of comparative literature include: comparative social sciences clusters, comparative natural sciences clusters, comparative interdisciplinary sciences clusters, and so on. Among them, comparative social sciences clusters include: comparative literature, comparative history, comparative philosophy, and so on; comparative natural sciences clusters include: comparative mathematics, comparative physics, comparative chemistry, comparative medicine, comparative biology, and so on.

  14. bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

    Science.gov (United States)

    Alexander, Nathan; Woetzel, Nils; Meiler, Jens

    2011-02-01

    Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

  15. Quantum chemical study of the structure, spectroscopy and reactivity of NO+.(H2O) n=1-5 clusters.

    Science.gov (United States)

    Linton, Kirsty A; Wright, Timothy G; Besley, Nicholas A

    2018-03-13

    Quantum chemical methods including Møller-Plesset perturbation (MP2) theory and density functional theory (DFT) have been used to study the structure, spectroscopy and reactivity of NO + (H 2 O) n =1-5 clusters. MP2/6-311++G** calculations are shown to describe the structure and spectroscopy of the clusters well. DFT calculations with exchange-correlation functionals with a low fraction of Hartree-Fock exchange give a binding energy of NO + (H 2 O) that is too high and incorrectly predict the lowest energy structure of NO + (H 2 O) 2 , and this error may be associated with a delocalization of charge onto the water molecule directly binding to NO + Ab initio molecular dynamics (AIMD) simulations were performed to study the NO + (H 2 O) 5 [Formula: see text] H + (H 2 O) 4 + HONO reaction to investigate the formation of HONO from NO + (H 2 O) 5 Whether an intracluster reaction to form HONO is observed depends on the level of electronic structure theory used. Of note is that methods that accurately describe the relative energies of the product and reactant clusters did not show reactions on the timescales studied. This suggests that in the upper atmosphere the reaction may occur owing to the energy present in the NO + (H 2 O) 5 complex following its formation.This article is part of the theme issue 'Modern theoretical chemistry'. © 2018 The Author(s).

  16. Domino effects within a chemical cluster: a game-theoretical modeling approach by using Nash-equilibrium.

    Science.gov (United States)

    Reniers, Genserik; Dullaert, Wout; Karel, Soudan

    2009-08-15

    Every company situated within a chemical cluster faces domino effect risks, whose magnitude depends on every company's own risk management strategies and on those of all others. Preventing domino effects is therefore very important to avoid catastrophes in the chemical process industry. Given that chemical companies are interlinked by domino effect accident links, there is some likelihood that even if certain companies fully invest in domino effects prevention measures, they can nonetheless experience an external domino effect caused by an accident which occurred in another chemical enterprise of the cluster. In this article a game-theoretic approach to interpret and model behaviour of chemical plants within chemical clusters while negotiating and deciding on domino effects prevention investments is employed.

  17. No Evidence of Chemical Abundance Variations in the Intermediate-age Cluster NGC 1783

    Science.gov (United States)

    Zhang, Hao; de Grijs, Richard; Li, Chengyuan; Wu, Xiaohan

    2018-02-01

    We have analyzed multi-passband photometric observations, obtained with the Hubble Space Telescope, of the massive (1.8 × 105 M ⊙), intermediate-age (1.8 Gyr-old) Large Magellanic Cloud star cluster NGC 1783. The morphology of the cluster’s red giant branch does not exhibit a clear broadening beyond its intrinsic width; the observed width is consistent with that owing to photometric uncertainties alone and independent of the photometric selection boundaries we applied to obtain our sample of red giant stars. The color dispersion of the cluster’s red giant stars around the best-fitting ridgeline is 0.062 ± 0.009 mag, which is equivalent to the width of 0.080 ± 0.001 mag derived from artificial simple stellar population tests, that is, tests based on single-age, single-metallicity stellar populations. NGC 1783 is comparably as massive as other star clusters that show clear evidence of multiple stellar populations. After incorporating mass-loss recipes from its current age of 1.8 Gyr to an age of 6 Gyr, NGC 1783 is expected to remain as massive as some other clusters that host clear multiple populations at these intermediate ages. If we were to assume that mass is an important driver of multiple population formation, then NGC 1783 should have exhibited clear evidence of chemical abundance variations. However, our results support the absence of any chemical abundance variations in NGC 1783.

  18. Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

    Science.gov (United States)

    Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

    2017-07-01

    Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

  19. Clustering of samples and elements based on multi-variable chemical data

    International Nuclear Information System (INIS)

    Op de Beeck, J.

    1984-01-01

    Clustering and classification are defined in the context of multivariable chemical analysis data. Classical multi-variate techniques, commonly used to interpret such data, are shown to be based on probabilistic and geometrical principles which are not justified for analytical data, since in that case one assumes or expects a system of more or less systematically related objects (samples) as defined by measurements on more or less systematically interdependent variables (elements). For the specific analytical problem of data set concerning a large number of trace elements determined in a large number of samples, a deterministic cluster analysis can be used to develop the underlying classification structure. Three main steps can be distinguished: diagnostic evaluation and preprocessing of the raw input data; computation of a symmetric matrix with pairwise standardized dissimilarity values between all possible pairs of samples and/or elements; and ultrametric clustering strategy to produce the final classification as a dendrogram. The software packages designed to perform these tasks are discussed and final results are given. Conclusions are formulated concerning the dangers of using multivariate, clustering and classification software packages as a black-box

  20. Chemical Bonding of Transition-Metal Co13 Clusters with Graphene.

    Science.gov (United States)

    Alonso-Lanza, Tomás; Ayuela, Andrés; Aguilera-Granja, Faustino

    2015-12-01

    We carried out density functional calculations to study the adsorption of Co13 clusters on graphene. Several free isomers were deposited at different positions with respect to the hexagonal lattice nodes, allowing us to study even the hcp 2d isomer, which was recently obtained as the most stable one. Surprisingly, the Co13 clusters attached to graphene prefer icosahedron-like structures in which the low-lying isomer is much distorted; in such structures, they are linked with more bonds than those reported in previous works. For any isomer, the most stable position binds to graphene by the Co atoms that can lose electrons. We find that the charge transfer between graphene and the clusters is small enough to conclude that the Co-graphene binding is not ionic-like but chemical. Besides, the same order of stability among the different isomers on doped graphene is kept. These findings could also be of interest for magnetic clusters on graphenic nanostructures such as ribbons and nanotubes. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  2. A model-based clustering method to detect infectious disease transmission outbreaks from sequence variation.

    Directory of Open Access Journals (Sweden)

    Rosemary M McCloskey

    2017-11-01

    Full Text Available Clustering infections by genetic similarity is a popular technique for identifying potential outbreaks of infectious disease, in part because sequences are now routinely collected for clinical management of many infections. A diverse number of nonparametric clustering methods have been developed for this purpose. These methods are generally intuitive, rapid to compute, and readily scale with large data sets. However, we have found that nonparametric clustering methods can be biased towards identifying clusters of diagnosis-where individuals are sampled sooner post-infection-rather than the clusters of rapid transmission that are meant to be potential foci for public health efforts. We develop a fundamentally new approach to genetic clustering based on fitting a Markov-modulated Poisson process (MMPP, which represents the evolution of transmission rates along the tree relating different infections. We evaluated this model-based method alongside five nonparametric clustering methods using both simulated and actual HIV sequence data sets. For simulated clusters of rapid transmission, the MMPP clustering method obtained higher mean sensitivity (85% and specificity (91% than the nonparametric methods. When we applied these clustering methods to published sequences from a study of HIV-1 genetic clusters in Seattle, USA, we found that the MMPP method categorized about half (46% as many individuals to clusters compared to the other methods. Furthermore, the mean internal branch lengths that approximate transmission rates were significantly shorter in clusters extracted using MMPP, but not by other methods. We determined that the computing time for the MMPP method scaled linearly with the size of trees, requiring about 30 seconds for a tree of 1,000 tips and about 20 minutes for 50,000 tips on a single computer. This new approach to genetic clustering has significant implications for the application of pathogen sequence analysis to public health, where

  3. Semiclassical methods in chemical reaction dynamics

    International Nuclear Information System (INIS)

    Keshavamurthy, S.

    1994-12-01

    Semiclassical approximations, simple as well as rigorous, are formulated in order to be able to describe gas phase chemical reactions in large systems. We formulate a simple but accurate semiclassical model for incorporating multidimensional tunneling in classical trajectory simulations. This model is based on the existence of locally conserved actions around the saddle point region on a multidimensional potential energy surface. Using classical perturbation theory and monitoring the imaginary action as a function of time along a classical trajectory we calculate state-specific unimolecular decay rates for a model two dimensional potential with coupling. Results are in good comparison with exact quantum results for the potential over a wide range of coupling constants. We propose a new semiclassical hybrid method to calculate state-to-state S-matrix elements for bimolecular reactive scattering. The accuracy of the Van Vleck-Gutzwiller propagator and the short time dynamics of the system make this method self-consistent and accurate. We also go beyond the stationary phase approximation by doing the resulting integrals exactly (numerically). As a result, classically forbidden probabilties are calculated with purely real time classical trajectories within this approach. Application to the one dimensional Eckart barrier demonstrates the accuracy of this approach. Successful application of the semiclassical hybrid approach to collinear reactive scattering is prevented by the phenomenon of chaotic scattering. The modified Filinov approach to evaluating the integrals is discussed, but application to collinear systems requires a more careful analysis. In three and higher dimensional scattering systems, chaotic scattering is suppressed and hence the accuracy and usefulness of the semiclassical method should be tested for such systems

  4. Semiclassical methods in chemical reaction dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Keshavamurthy, Srihari [Univ. of California, Berkeley, CA (United States)

    1994-12-01

    Semiclassical approximations, simple as well as rigorous, are formulated in order to be able to describe gas phase chemical reactions in large systems. We formulate a simple but accurate semiclassical model for incorporating multidimensional tunneling in classical trajectory simulations. This model is based on the existence of locally conserved actions around the saddle point region on a multidimensional potential energy surface. Using classical perturbation theory and monitoring the imaginary action as a function of time along a classical trajectory we calculate state-specific unimolecular decay rates for a model two dimensional potential with coupling. Results are in good comparison with exact quantum results for the potential over a wide range of coupling constants. We propose a new semiclassical hybrid method to calculate state-to-state S-matrix elements for bimolecular reactive scattering. The accuracy of the Van Vleck-Gutzwiller propagator and the short time dynamics of the system make this method self-consistent and accurate. We also go beyond the stationary phase approximation by doing the resulting integrals exactly (numerically). As a result, classically forbidden probabilties are calculated with purely real time classical trajectories within this approach. Application to the one dimensional Eckart barrier demonstrates the accuracy of this approach. Successful application of the semiclassical hybrid approach to collinear reactive scattering is prevented by the phenomenon of chaotic scattering. The modified Filinov approach to evaluating the integrals is discussed, but application to collinear systems requires a more careful analysis. In three and higher dimensional scattering systems, chaotic scattering is suppressed and hence the accuracy and usefulness of the semiclassical method should be tested for such systems.

  5. A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

    Science.gov (United States)

    Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

    2016-02-01

    Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

  6. The Views of Turkish Pre-Service Teachers about Effectiveness of Cluster Method as a Teaching Writing Method

    Science.gov (United States)

    Kitis, Emine; Türkel, Ali

    2017-01-01

    The aim of this study is to find out Turkish pre-service teachers' views on effectiveness of cluster method as a writing teaching method. The Cluster Method can be defined as a connotative creative writing method. The way the method works is that the person who brainstorms on connotations of a word or a concept in abscence of any kind of…

  7. Chemical Abundances of Red Giant Stars in the Globular Cluster M107 (NGC 6171)

    Science.gov (United States)

    O'Connell, Julia E.; Johnson, Christian I.; Pilachowski, Catherine A.; Burks, Geoffrey

    2011-10-01

    We present chemical abundances of Al and several Fe-Peak and neutron-capture elements for 13 red giant branch stars in the Galactic globular cluster NGC 6171 (M107). The abundances were determined using equivalent width and spectrum synthesis analyses of moderate-resolution ( R ˜ 15,000), moderate signal-to-noise ratio ( ˜ 80) spectra obtained with the WIYN telescope and Hydra multifiber spectrograph. A comparison between photometric and spectroscopic effective temperature estimates seems to indicate that a reddening value of E(B - V) = 0.46 may be more appropriate for this cluster than the more commonly used value of E(B - V) = 0.33. Similarly, we found that a distance modulus of (m - M)V ≈ 13.7 provided reasonable surface gravity estimates for the stars in our sample. Our spectroscopic analysis finds M107 to be moderately metal-poor with = -0.93 and also exhibits a small star-to-star metallicity dispersion (σ = 0.04). These results are consistent with previous photometric and spectroscopic studies. Aluminum appears to be moderately enhanced in all program stars ( = +0.39, σ = 0.11). The relatively small star-to-star scatter in [Al/Fe] differs from the trend found in more metal-poor globular clusters, and is more similar to what is found in clusters with [Fe/H] ≳ -1. The cluster also appears to be moderately r-process-enriched with = +0.32 (σ = 0.17).

  8. Investigating hydrogel dosimeter decomposition by chemical methods

    International Nuclear Information System (INIS)

    Jordan, Kevin

    2015-01-01

    The chemical oxidative decomposition of leucocrystal violet micelle hydrogel dosimeters was investigated using the reaction of ferrous ions with hydrogen peroxide or sodium bicarbonate with hydrogen peroxide. The second reaction is more effective at dye decomposition in gelatin hydrogels. Additional chemical analysis is required to determine the decomposition products

  9. Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

    Directory of Open Access Journals (Sweden)

    Yimei Wang

    2018-04-01

    Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

  10. A Detailed Study of Chemical Enrichment History of Galaxy Clusters out to Virial Radius

    Science.gov (United States)

    Loewenstein, Michael

    The origin of the metal enrichment of the intracluster medium (ICM) represents a fundamental problem in extragalactic astrophysics, with implications for our understanding of how stars and galaxies form, the nature of Type Ia supernova (SNIa) progenitors, and the thermal history of the ICM. These heavy elements are ultimately synthesized by supernova (SN) explosions; however, the details of the sites of metal production and mechanisms that transport metals to the ICM remain unclear. To make progress, accurate abundance profiles for multiple elements extending from the cluster core out to the virial radius (r180) are required for a significant cluster sample. We propose an X-ray spectroscopic study of a carefully-chosen sample of archival Suzaku and XMM-Newton observations of 23 clusters: XMM-Newton data probe the cluster temperature and abundances out to (0.5-1)r500, while Suzaku data probe the cluster outskirts. A method devised by our team to utilize all elements with emission lines in the X-ray bandpass to measure the relative contributions of supernova explosions by direct modeling of their X-ray spectra will be applied in order to constrain the demographics of the enriching supernova population. In addition we will conduct a stacking analysis of our already existing Suzaku and XMM-Newton cluster spectra to search for weak emssion lines that are important SN diagnostics, and to look for trends with cluster mass and redshift. The funding we propose here will also support the data analysis of our recent Suzaku observations of the archetypal cluster A3112 (200 ks each on the core and outskirts). Our data analysis, intepreted using theoretical models we have developed, will enable us to constrain the star formation history, SN demographics, and nature of SNIa progenitors associated with galaxy cluster stellar populations - and, hence, directly addresess NASA s Strategic Objective 2.4.2 in Astrophysics that aims to improve the understanding of how the Universe works

  11. Motion estimation using point cluster method and Kalman filter.

    Science.gov (United States)

    Senesh, M; Wolf, A

    2009-05-01

    The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal

  12. AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

    Directory of Open Access Journals (Sweden)

    Cooper James B

    2010-03-01

    Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

  13. Chemical Reactivity as Described by Quantum Chemical Methods

    Directory of Open Access Journals (Sweden)

    F. De Proft

    2002-04-01

    Full Text Available Abstract: Density Functional Theory is situated within the evolution of Quantum Chemistry as a facilitator of computations and a provider of new, chemical insights. The importance of the latter branch of DFT, conceptual DFT is highlighted following Parr's dictum "to calculate a molecule is not to understand it". An overview is given of the most important reactivity descriptors and the principles they are couched in. Examples are given on the evolution of the structure-property-wave function triangle which can be considered as the central paradigm of molecular quantum chemistry to (for many purposes a structure-property-density triangle. Both kinetic as well as thermodynamic aspects can be included when further linking reactivity to the property vertex. In the field of organic chemistry, the ab initio calculation of functional group properties and their use in studies on acidity and basicity is discussed together with the use of DFT descriptors to study the kinetics of SN2 reactions and the regioselectivity in Diels Alder reactions. Similarity in reactivity is illustrated via a study on peptide isosteres. In the field of inorganic chemistry non empirical studies of adsorption of small molecules in zeolite cages are discussed providing Henry constants and separation constants, the latter in remarkable good agreement with experiments. Possible refinements in a conceptual DFT context are presented. Finally an example from biochemistry is discussed : the influence of point mutations on the catalytic activity of subtilisin.

  14. Chemical pre-processing of cluster galaxies over the past 10 billion years in the IllustrisTNG simulations

    Science.gov (United States)

    Gupta, Anshu; Yuan, Tiantian; Torrey, Paul; Vogelsberger, Mark; Martizzi, Davide; Tran, Kim-Vy H.; Kewley, Lisa J.; Marinacci, Federico; Nelson, Dylan; Pillepich, Annalisa; Hernquist, Lars; Genel, Shy; Springel, Volker

    2018-06-01

    We use the IllustrisTNG simulations to investigate the evolution of the mass-metallicity relation (MZR) for star-forming cluster galaxies as a function of the formation history of their cluster host. The simulations predict an enhancement in the gas-phase metallicities of star-forming cluster galaxies (109 cluster galaxies appears prior to their infall into the central cluster potential, indicating for the first time a systematic `chemical pre-processing' signature for infalling cluster galaxies. Namely, galaxies that will fall into a cluster by z = 0 show a ˜0.05 dex enhancement in the MZR compared to field galaxies at z ≤ 0.5. Based on the inflow rate of gas into cluster galaxies and its metallicity, we identify that the accretion of pre-enriched gas is the key driver of the chemical evolution of such galaxies, particularly in the stellar mass range (109 clusters. Our results motivate future observations looking for pre-enrichment signatures in dense environments.

  15. Chemical Abundances of Red Giant Branch Stars in the Globular Cluster NGC 288

    Science.gov (United States)

    Hsyu, Tiffany; Johnson, C. I.; Pilachowski, C. A.; Lee, Y.; Rich, R. M.

    2013-01-01

    We present chemical abundances and radial velocities for ~30 red giant branch (RGB) stars in the globular cluster NGC 288. The results are based on moderate resolution (R≈18,000) and moderate signal-to-noise ratio 50-75) obtained with the Hydra multi-object spectrograph on the Blanco 4m telescope. NGC 288 has been shown to exhibit two separate RGBs and we investigate possible differences in metallicity and/or light element abundances between stars on each branch. We present a new filter tracing for the CTIO Calcium HK narrow band filter and explore its effects on previous globular cluster color-magnitude diagrams. We also compare the light element abundance patterns of NGC 288 to those of other similar metallicity halo clusters. This material is based upon work supported by the National Science Foundation under award No.AST-1003201 to C.I.J. C.A.P. gratefully acknowledges support from the Daniel Kirkwood Research Fund at Indiana University. R.M.R. acknowledges support from NSF grants AST-0709479 and AST-121120995.

  16. Domino effects within a chemical cluster : A game-theoretical modeling approach by using Nash-equilibrium

    NARCIS (Netherlands)

    Reniers, Genserik; Dullaert, Wout; Karel, Soudan

    2009-01-01

    Every company situated within a chemical cluster faces domino effect risks, whose magnitude depends on every company's own risk management strategies and on those of all others. Preventing domino effects is therefore very important to avoid catastrophes in the chemical process industry. Given that

  17. The chemical composition of a regular halo globular cluster: NGC 5897

    Science.gov (United States)

    Koch, Andreas; McWilliam, Andrew

    2014-05-01

    We report for the first time on the chemical composition of the halo cluster NGC 5897 (R⊙ = 12.5 kpc), based on chemical abundance ratios for 27 α-, iron-peak, and neutron-capture elements in seven red giants. From our high-resolution, high signal-to-noise spectra obtained with the Magellan/MIKE spectrograph, we find a mean iron abundance from the neutral species of [Fe/H] = - 2.04 ± 0.01 (stat.) ± 0.15 (sys.), which is more metal-poor than implied by previous photometric and low-resolution spectroscopic studies. The cluster NGC 5897 is α-enhanced (to 0.34 ± 0.01 dex) and shows Fe-peak element ratios typical of other (metal-poor) halo globular clusters (GCs) with no overall, significant abundance spreads in iron or in any other heavy element. Like other GCs, NGC 5897 shows a clear Na-O anti-correlation, where we find a prominent primordial population of stars with enhanced O abundances and approximately solar Na/Fe ratios, while two stars are Na-rich, providing chemical proof of the presence of multiple populations in this cluster. Comparison of the heavy element abundances with the solar-scaled values and the metal-poor GC M15 from the literature confirms that NGC 5897 has experienced little contribution from s-process nucleosynthesis. One star of the first generation stands out in that it shows very low La and Eu abundances. Overall, NGC 5897 is a well behaved GC showing archetypical correlations and element-patterns, with little room for surprises in our data. We suggest that its lower metallicity could explain the unusually long periods of RR Lyr that were found in NGC 5897. This paper includes data gathered with the 6.5-m Magellan Telescopes located at Las Campanas Observatory, Chile.Table 5 is available in electronic form at http://www.aanda.orgFull Table 2 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/565/A23

  18. Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

    Directory of Open Access Journals (Sweden)

    Susan Worner

    2013-09-01

    Full Text Available For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM, a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k

  19. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... Author for correspondence (zh4403701@126.com). MS received 15 ... lic clusters using density functional theory (DFT)-GGA of the DMOL3 package. ... In the process of geometric optimization, con- vergence thresholds ..... and Postgraduate Research & Practice Innovation Program of. Jiangsu Province ...

  20. clusters

    Indian Academy of Sciences (India)

    environmental as well as technical problems during fuel gas utilization. ... adsorption on some alloys of Pd, namely PdAu, PdAg ... ried out on small neutral and charged Au24,26,27, Cu,28 ... study of Zanti et al.29 on Pdn (n = 1–9) clusters.

  1. An external domino effects investment approach to improve cross-plant safety within chemical clusters

    International Nuclear Information System (INIS)

    Reniers, Genserik

    2010-01-01

    Every company situated within a chemical cluster faces the risk of being struck by an escalating accident at one of its neighbouring plants (the so-called external domino effect risks). These cross-plant risks can be reduced or eliminated if neighbouring companies are willing to invest in systems and measures to prevent them. However, since reducing such multi-plant risks does not lead to direct economic benefits, enterprises tend to be reluctant to invest more than needed for meeting minimal legal requirements and they tend to invest without collaborating. The suggested approach in this article indicates what information is required to evaluate the available investment options in external domino effects prevention. To this end, game theory is used as a promising scientific technique to investigate the decision-making process on investments in prevention measures simultaneously involving several plants. The game between two neighbouring chemical plants and their strategic investment behaviour regarding the prevention of external domino effects is described and an illustrative example is provided. Recommendations are formulated to advance cross-plant prevention investments in a two-company cluster.

  2. An external domino effects investment approach to improve cross-plant safety within chemical clusters.

    Science.gov (United States)

    Reniers, Genserik

    2010-05-15

    Every company situated within a chemical cluster faces the risk of being struck by an escalating accident at one of its neighbouring plants (the so-called external domino effect risks). These cross-plant risks can be reduced or eliminated if neighbouring companies are willing to invest in systems and measures to prevent them. However, since reducing such multi-plant risks does not lead to direct economic benefits, enterprises tend to be reluctant to invest more than needed for meeting minimal legal requirements and they tend to invest without collaborating. The suggested approach in this article indicates what information is required to evaluate the available investment options in external domino effects prevention. To this end, game theory is used as a promising scientific technique to investigate the decision-making process on investments in prevention measures simultaneously involving several plants. The game between two neighbouring chemical plants and their strategic investment behaviour regarding the prevention of external domino effects is described and an illustrative example is provided. Recommendations are formulated to advance cross-plant prevention investments in a two-company cluster. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  3. Differences Between Ward's and UPGMA Methods of Cluster Analysis: Implications for School Psychology.

    Science.gov (United States)

    Hale, Robert L.; Dougherty, Donna

    1988-01-01

    Compared the efficacy of two methods of cluster analysis, the unweighted pair-groups method using arithmetic averages (UPGMA) and Ward's method, for students grouped on intelligence, achievement, and social adjustment by both clustering methods. Found UPGMA more efficacious based on output, on cophenetic correlation coefficients generated by each…

  4. Developing cluster strategy of apples dodol SMEs by integration K-means clustering and analytical hierarchy process method

    Science.gov (United States)

    Mustaniroh, S. A.; Effendi, U.; Silalahi, R. L. R.; Sari, T.; Ala, M.

    2018-03-01

    The purposes of this research were to determine the grouping of apples dodol small and medium enterprises (SMEs) in Batu City and to determine an appropriate development strategy for each cluster. The methods used for clustering SMEs was k-means. The Analytical Hierarchy Process (AHP) approach was then applied to determine the development strategy priority for each cluster. The variables used in grouping include production capacity per month, length of operation, investment value, average sales revenue per month, amount of SMEs assets, and the number of workers. Several factors were considered in AHP include industry cluster, government, as well as related and supporting industries. Data was collected using the methods of questionaire and interviews. SMEs respondents were selected among SMEs appels dodol in Batu City using purposive sampling. The result showed that two clusters were formed from five apples dodol SMEs. The 1stcluster of apples dodol SMEs, classified as small enterprises, included SME A, SME C, and SME D. The 2ndcluster of SMEs apples dodol, classified as medium enterprises, consisted of SME B and SME E. The AHP results indicated that the priority development strategy for the 1stcluster of apples dodol SMEs was improving quality and the product standardisation, while for the 2nd cluster was increasing the marketing access.

  5. Swarm: robust and fast clustering method for amplicon-based studies

    Science.gov (United States)

    Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

    2014-01-01

    Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. PMID:25276506

  6. Swarm: robust and fast clustering method for amplicon-based studies

    Directory of Open Access Journals (Sweden)

    Frédéric Mahé

    2014-09-01

    Full Text Available Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.

  7. CHEMICAL ABUNDANCES IN NGC 5053: A VERY METAL-POOR AND DYNAMICALLY COMPLEX GLOBULAR CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico [Astronomy Department, Indiana University, Bloomington, IN 47405 (United States)

    2015-05-10

    NGC 5053 provides a rich environment to test our understanding of the complex evolution of globular clusters (GCs). Recent studies have found that this cluster has interesting morphological features beyond the typical spherical distribution of GCs, suggesting that external tidal effects have played an important role in its evolution and current properties. Additionally, simulations have shown that NGC 5053 could be a likely candidate to belong to the Sagittarius dwarf galaxy (Sgr dSph) stream. Using the Wisconsin–Indiana–Yale–NOAO–Hydra multi-object spectrograph, we have collected high quality (signal-to-noise ratio ∼ 75–90), medium-resolution spectra for red giant branch stars in NGC 5053. Using these spectra we have measured the Fe, Ca, Ti, Ni, Ba, Na, and O abundances in the cluster. We measure an average cluster [Fe/H] abundance of −2.45 with a standard deviation of 0.04 dex, making NGC 5053 one of the most metal-poor GCs in the Milky Way (MW). The [Ca/Fe], [Ti/Fe], and [Ba/Fe] we measure are consistent with the abundances of MW halo stars at a similar metallicity, with alpha-enhanced ratios and slightly depleted [Ba/Fe]. The Na and O abundances show the Na–O anti-correlation found in most GCs. From our abundance analysis it appears that NGC 5053 is at least chemically similar to other GCs found in the MW. This does not, however, rule out NGC 5053 being associated with the Sgr dSph stream.

  8. Chemical Abundances in NGC 5053: A Very Metal-poor and Dynamically Complex Globular Cluster

    Science.gov (United States)

    Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico

    2015-05-01

    NGC 5053 provides a rich environment to test our understanding of the complex evolution of globular clusters (GCs). Recent studies have found that this cluster has interesting morphological features beyond the typical spherical distribution of GCs, suggesting that external tidal effects have played an important role in its evolution and current properties. Additionally, simulations have shown that NGC 5053 could be a likely candidate to belong to the Sagittarius dwarf galaxy (Sgr dSph) stream. Using the Wisconsin-Indiana-Yale-NOAO-Hydra multi-object spectrograph, we have collected high quality (signal-to-noise ratio ˜ 75-90), medium-resolution spectra for red giant branch stars in NGC 5053. Using these spectra we have measured the Fe, Ca, Ti, Ni, Ba, Na, and O abundances in the cluster. We measure an average cluster [Fe/H] abundance of -2.45 with a standard deviation of 0.04 dex, making NGC 5053 one of the most metal-poor GCs in the Milky Way (MW). The [Ca/Fe], [Ti/Fe], and [Ba/Fe] we measure are consistent with the abundances of MW halo stars at a similar metallicity, with alpha-enhanced ratios and slightly depleted [Ba/Fe]. The Na and O abundances show the Na-O anti-correlation found in most GCs. From our abundance analysis it appears that NGC 5053 is at least chemically similar to other GCs found in the MW. This does not, however, rule out NGC 5053 being associated with the Sgr dSph stream.

  9. Computational studies of atmospherically-relevant chemical reactions in water clusters and on liquid water and ice surfaces.

    Science.gov (United States)

    Gerber, R Benny; Varner, Mychel E; Hammerich, Audrey D; Riikonen, Sampsa; Murdachaew, Garold; Shemesh, Dorit; Finlayson-Pitts, Barbara J

    2015-02-17

    CONSPECTUS: Reactions on water and ice surfaces and in other aqueous media are ubiquitous in the atmosphere, but the microscopic mechanisms of most of these processes are as yet unknown. This Account examines recent progress in atomistic simulations of such reactions and the insights provided into mechanisms and interpretation of experiments. Illustrative examples are discussed. The main computational approaches employed are classical trajectory simulations using interaction potentials derived from quantum chemical methods. This comprises both ab initio molecular dynamics (AIMD) and semiempirical molecular dynamics (SEMD), the latter referring to semiempirical quantum chemical methods. Presented examples are as follows: (i) Reaction of the (NO(+))(NO3(-)) ion pair with a water cluster to produce the atmospherically important HONO and HNO3. The simulations show that a cluster with four water molecules describes the reaction. This provides a hydrogen-bonding network supporting the transition state. The reaction is triggered by thermal structural fluctuations, and ultrafast changes in atomic partial charges play a key role. This is an example where a reaction in a small cluster can provide a model for a corresponding bulk process. The results support the proposed mechanism for production of HONO by hydrolysis of NO2 (N2O4). (ii) The reactions of gaseous HCl with N2O4 and N2O5 on liquid water surfaces. Ionization of HCl at the water/air interface is followed by nucleophilic attack of Cl(-) on N2O4 or N2O5. Both reactions proceed by an SN2 mechanism. The products are ClNO and ClNO2, precursors of atmospheric atomic chlorine. Because this mechanism cannot result from a cluster too small for HCl ionization, an extended water film model was simulated. The results explain ClNO formation experiments. Predicted ClNO2 formation is less efficient. (iii) Ionization of acids at ice surfaces. No ionization is found on ideal crystalline surfaces, but the process is efficient on

  10. Risk perception of aquatic pollution originated from chemical industry clusters in the coastal area of Jiangsu province, China.

    Science.gov (United States)

    Yao, Hong; Liu, Bo; You, Zhen; Zhao, Li

    2018-02-01

    According to "the Layout Scheme of the Chemical Industry in Jiangsu Province From 2016 to 2030" and "the Development Planning in the Coastal Area of Jiangsu Province, China," several chemical industry clusters will be located in the coastal area of Jiangsu province, China, and the risk of surface water pollution will be inevitably higher in the densely populated region. To get to know the risk acceptance level of the residents near the clusters, public perception was analyzed from the five risk factors: the basic knowledge about the pollution, the negative effects on aquatic environment imposed by the clusters, the positive effects brought by the clusters, the trust of controlling aquatic pollution, and the acceptance of the clusters. Twenty-four statements were screened out to describe the five factors, and about 600 residents were covered in three typical clusters surveyed. On the whole, the youth showed a higher interest on the survey, and middle-aged people were likely to be more concerned about aquatic pollution incident. There was no significant difference on risk perception of the three clusters. The respondents investigated had good knowledge background on aquatic pollution and the residents identified with the benefits brought by the clusters. They were weak in risk awareness of pollution originated from the chemical enterprises' groups. Although the respondents regarded that chemical industry clusters did not expose all points of pollutants' generation to the public, they inclined to trust the administration agencies on controlling the pollution and welcome the construction of chemical clusters in their dwelling cities. Besides, risk perception showed obvious spatial distribution. The closer were the samples' sites to the clusters and the rivers receiving pollutants, the higher were the residents' perceived risk, benefit, and trust. However, there was no identical spatial difference on risk acceptance, which might be comprehensively influenced by various

  11. Cluster-cell calculation using the method of generalized homogenization

    International Nuclear Information System (INIS)

    Laletin, N.I.; Boyarinov, V.F.

    1988-01-01

    The generalized-homogenization method (GHM), used for solving the neutron transfer equation, was applied to calculating the neutron distribution in the cluster cell with a series of cylindrical cells with cylindrically coaxial zones. Single-group calculations of the technological channel of the cell of an RBMK reactor were performed using GHM. The technological channel was understood to be the reactor channel, comprised of the zirconium rod, the water or steam-water mixture, the uranium dioxide fuel element, and the zirconium tube, together with the adjacent graphite layer. Calculations were performed for channels with no internal sources and with unit incoming current at the external boundary as well as for channels with internal sources and zero current at the external boundary. The PRAKTINETs program was used to calculate the symmetric neutron distributions in the microcell and in channels with homogenized annular zones. The ORAR-TsM program was used to calculate the antisymmetric distribution in the microcell. The accuracy of the calculations were compared for the two channel versions

  12. The Cluster Variation Method: A Primer for Neuroscientists.

    Science.gov (United States)

    Maren, Alianna J

    2016-09-30

    Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables , is defined in terms of a single interaction enthalpy parameter ( h ) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

  13. The Cluster Variation Method: A Primer for Neuroscientists

    Directory of Open Access Journals (Sweden)

    Alianna J. Maren

    2016-09-01

    Full Text Available Effective Brain–Computer Interfaces (BCIs require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h for the case of an equiprobable distribution of bistate (neural/neural ensemble units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

  14. Rich Ground State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters

    DEFF Research Database (Denmark)

    Larsen, Peter Mahler; Jacobsen, Karsten Wedel; Schiøtz, Jakob

    2018-01-01

    We show that nanoparticles can have very rich ground state chemical order. This is illustrated by determining the chemical ordering of Ag-Au 309-atom Mackay icosahedral nanoparticles. The energy of the nanoparticles is described using a cluster expansion model, and a Mixed Integer Programming (MIP......) approach is used to find the exact ground state configurations for all stoichiometries. The chemical ordering varies widely between the different stoichiometries, and display a rich zoo of structures with non-trivial ordering....

  15. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

  16. Comparative analysis of clustering methods for gene expression time course data

    Directory of Open Access Journals (Sweden)

    Ivan G. Costa

    2004-01-01

    Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

  17. Assessment of chemical exposures: calculation methods for environmental professionals

    National Research Council Canada - National Science Library

    Daugherty, Jack E

    1997-01-01

    ... on by scientists, businessmen, and policymakers. Assessment of Chemical Exposures: Calculation Methods for Environmental Professionals addresses the expanding scope of exposure assessments in both the workplace and environment...

  18. Improvement of economic potential estimation methods for enterprise with potential branch clusters use

    Directory of Open Access Journals (Sweden)

    V.Ya. Nusinov

    2017-08-01

    Full Text Available The research determines that the current existing methods of enterprise’s economic potential estimation are based on the use of additive, multiplicative and rating models. It is determined that the existing methods have a row of defects. For example, not all the methods take into account the branch features of the analysis, and also the level of development of the enterprise comparatively with other enterprises. It is suggested to level such defects by an account at the estimation of potential integral level not only by branch features of enterprises activity but also by the intra-account economic clusterization of such enterprises. Scientific works which are connected with the using of clusters for the estimation of economic potential are generalized. According to the results of generalization it is determined that it is possible to distinguish 9 scientific approaches in this direction: the use of natural clusterization of enterprises with the purpose of estimation and increase of region potential; the use of natural clusterization of enterprises with the purpose of estimation and increase of industry potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of region potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of industry potential; the use of artificial clusterization of enterprises with the purpose of clustering potential estimation; the use of artificial clusterization of enterprises with the purpose of estimation of clustering competitiveness potential; the use of natural (artificial clusterization for the estimation of clustering efficiency; the use of natural (artificial clusterization for the increase of level at region (industries development; the use of methods of economic potential of region (industries estimation or its constituents for the construction of the clusters. It is determined that the use of clusterization method in

  19. Device for collecting chemical compounds and related methods

    Science.gov (United States)

    Scott, Jill R.; Groenewold, Gary S.; Rae, Catherine

    2013-01-01

    A device for sampling chemical compounds from fixed surfaces and related methods are disclosed. The device may include a vacuum source, a chamber and a sorbent material. The device may utilize vacuum extraction to volatilize the chemical compounds from the fixed surfaces so that they may be sorbed by the sorbent material. The sorbent material may then be analyzed using conventional thermal desorption/gas chromatography/mass spectrometry (TD/GC/MS) instrumentation to determine presence of the chemical compounds. The methods may include detecting release and presence of one or more chemical compounds and determining the efficacy of decontamination. The device may be useful in collection and analysis of a variety of chemical compounds, such as residual chemical warfare agents, chemical attribution signatures and toxic industrial chemicals.

  20. Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

    Science.gov (United States)

    Ing, Alex; Schwarzbauer, Christian

    2014-01-01

    Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

  1. Chemical degradation of selected Zn-based corrosion products induced by C{sub 60} cluster, Ar cluster and Ar{sup +} ion sputtering in the focus of X-ray photoelectron spectroscopy (XPS)

    Energy Technology Data Exchange (ETDEWEB)

    Steinberger, R., E-mail: roland.steinberger@jku.at [Christian Doppler Laboratory for Microscopic and Spectroscopic Material Characterization, Center for Surface and Nanoanalytics, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz (Austria); Sicking, J., E-mail: jens.sicking@bayer.com [Bayer AG, Engineering & Technology, Applied Physics, Chempark Building E 41, 51368 Leverkusen (Germany); Weise, J., E-mail: juliane.weise@physik.tu-freiberg.de [Institut für Experimentelle Physik, TU Bergakademie Freiberg, Leipziger Straße 23, 09599 Freiberg (Germany); Duchoslav, J., E-mail: jiri.duchoslav@jku.at [Christian Doppler Laboratory for Microscopic and Spectroscopic Material Characterization, Center for Surface and Nanoanalytics, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz (Austria); Greunz, T., E-mail: theresia.greunz@jku.at [Christian Doppler Laboratory for Microscopic and Spectroscopic Material Characterization, Center for Surface and Nanoanalytics, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz (Austria); Meyer, D.C., E-mail: Dirk-Carl.Meyer@physik.tu-freiberg.de [Institut für Experimentelle Physik, TU Bergakademie Freiberg, Leipziger Straße 23, 09599 Freiberg (Germany); Stifter, D., E-mail: david.stifter@jku.at [Christian Doppler Laboratory for Microscopic and Spectroscopic Material Characterization, Center for Surface and Nanoanalytics, Johannes Kepler University Linz, Altenberger Straße 69, 4040 Linz (Austria)

    2017-05-01

    Highlights: • XPS investigations for various sputter concepts on Zn-based corrosions products. • Direct comparison of induced chemical damage for ion and cluster sputtering. • Azimuthal rotation or heavy projectile bombardment was not found to be beneficial. • Ar cluster etching is rated as unsuitable for surface cleaning or depth profiling. • C{sub 60} and Ar{sup +} are applicable for sputtering when degradation is carefully considered. - Abstract: Monoatomic ion sputtering is a common concept for surface sensitive analysis methods to clean surfaces prior investigation or to obtain information from deeper regions. However, severe damage of the materials – linked to preferential sputtering, ion implantation, atomic mixing and in worst case chemical degradation – can affect the validity of the analysis. Hence, the impact of C{sub 60} cluster etching, furthermore, of Ar{sup +} ion bombardment with and without azimuthal sample rotation and also the application of heavy projectiles (Xe{sup +} ions) was investigated to find a concept, which is less destructive or with less critical influence on the chemical nature of the investigated materials. In this work the focus is set on hydrozincite and zinc oxide, two common corrosion products of Zn-based coatings. As a main point, all the obtained results from (i) Ar{sup +} ion, (ii) Ar cluster, and (iii) C{sub 60} cluster etching on the degradation kinetics of hydrozincite were compared with respect to the reached sputter depth. In addition, the sputter rate of all three methods was experimentally determined for ZnO. In total, fully non-destructive conditions could not be found, but valuable knowledge on the type and rate of degradation, which is essential to choose the most suited sputter concept.

  2. Safety in the Chemical Laboratory: Tested Disposal Methods for Chemical Wastes from Academic Laboratories.

    Science.gov (United States)

    Armour, M. A.; And Others

    1985-01-01

    Describes procedures for disposing of dichromate cleaning solution, picric acid, organic azides, oxalic acid, chemical spills, and hydroperoxides in ethers and alkenes. These methods have been tested under laboratory conditions and are specific for individual chemicals rather than for groups of chemicals. (JN)

  3. Chemical abundances in the globular clusters NGC6229 and NGC6779

    Science.gov (United States)

    Khamidullina, D. A.; Sharina, M. E.; Shimansky, V. V.; Davoust, E.

    2014-10-01

    Long-slit medium-resolution spectra of the Galactic globular clusters (GCs) NGC6229 and NGC6779, obtained with the CARELEC spectrograph at the 1.93-m telescope of the Haute-Provence observatory, have been used to determine the age, helium abundance (Y), and metallicity [Fe/H] as well as the first estimate of the abundances of C, N, O, Mg, Ca, Ti, and Cr for these objects. We solved this task by comparing the observed spectra and the integrated synthetic spectra, calculated with the use of the stellar atmosphere models with the parameters preset for the stars from these clusters. The model mass estimates, T eff, and log g were derived by comparing the observed "color-magnitude" diagrams and the theoretical isochrones. The summing-up of the synthetic blanketed stellar spectra was conducted according to the Chabrier mass function. To test the accuracy of the results, we estimated the chemical abundances, [Fe/H], log t, and Y for the NGC5904 and NGC6254 clusters, which, according to the literature, are considered to be the closest analogues of the two GCs of our study. Using the medium-resolution spectra from the library of Schiavon et al., we obtained for these two clusters a satisfactory agreement with the reported estimates for all the parameters within the errors. We derived the following cluster parameters. NGC6229: [Fe/H] = -1.65 dex, t = 12.6 Gyr, Y = 0.26, [ α/Fe] = 0.28 dex; NGC6779: [Fe/H] = -1.9 dex, t = 12.6 Gyr, Y = 0.23, [ α/Fe] = 0.08 dex; NGC5904: [Fe/H] = -1.6 dex, t = 12.6 Gyr, Y = 0.30, [ α/Fe] = 0.35 dex; NGC6254: [Fe/H] = -1.52 dex, t = 11.2 Gyr, Y = 0.30, [ α/Fe] = 0.025 dex. The value [ α/Fe] denotes the average of the Ca and Mg abundances.

  4. Atomic and electronic structure of clusters from car-Parrinello method

    International Nuclear Information System (INIS)

    Kumar, V.

    1994-06-01

    With the development of ab-initio molecular dynamics method, it has now become possible to study the static and dynamical properties of clusters containing up to a few tens of atoms. Here I present a review of the method within the framework of the density functional theory and pseudopotential approach to represent the electron-ion interaction and discuss some of its applications to clusters. Particular attention is focussed on the structure and bonding properties of clusters as a function of their size. Applications to clusters of alkali metals and Al, non-metal - metal transition in divalent metal clusters, molecular clusters of carbon and Sb are discussed in detail. Some results are also presented on mixed clusters. (author). 121 refs, 24 ifigs

  5. Chemical Method of Urine Volume Measurement

    Science.gov (United States)

    Petrack, P.

    1967-01-01

    A system has been developed and qualified as flight hardware for the measurement of micturition volumes voided by crewmen during Gemini missions. This Chemical Urine Volume Measurement System (CUVMS) is used for obtaining samples of each micturition for post-flight volume determination and laboratory analysis for chemical constituents of physiological interest. The system is versatile with respect to volumes measured, with a capacity beyond the largest micturition expected to be encountered, and with respect to mission duration of inherently indefinite length. The urine sample is used for the measurement of total micturition volume by a tracer dilution technique, in which a fixed, predetermined amount of tritiated water is introduced and mixed into the voided urine, and the resulting concentration of the tracer in the sample is determined with a liquid scintillation spectrometer. The tracer employed does not interfere with the analysis for the chemical constituents of the urine. The CUVMS hardware consists of a four-way selector valve in which an automatically operated tracer metering pump is incorporated, a collection/mixing bag, and tracer storage accumulators. The assembled system interfaces with a urine receiver at the selector valve inlet, sample bags which connect to the side of the selector valve, and a flexible hose which carries the excess urine to the overboard drain connection. Results of testing have demonstrated system volume measurement accuracy within the specification limits of +/-5%, and operating reliability suitable for system use aboard the GT-7 mission, in which it was first used.

  6. Time-of-flight secondary ion mass spectrometry with energetic cluster ion impact ionization for highly sensitive chemical structure characterization

    Energy Technology Data Exchange (ETDEWEB)

    Hirata, K., E-mail: k.hirata@aist.go.jp [National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565 (Japan); Saitoh, Y.; Chiba, A.; Yamada, K.; Narumi, K. [Takasaki Advanced Radiation Research Institute (TARRI), Japan Atomic Energy Agency (JAEA), Takasaki, Gumma 370-1292 (Japan)

    2013-11-01

    Energetic cluster ions with energies of the order of sub MeV or greater were applied to time-of-flight (TOF) secondary ion (SI) mass spectrometry. This gave various advantages including enhancement of SIs required for chemical structure characterization and prevention of charging effects in SI mass spectra for organic targets. We report some characteristic features of TOF SI mass spectrometry using energetic cluster ion impact ionization and discuss two future applications of it.

  7. Enhanced Electromagnetic and Chemical/Biological Sensing. Properties of Atomic Cluster-Derived Materials

    National Research Council Canada - National Science Library

    Schatz, George

    2003-01-01

    The Center for Atomic Clusters-derived Materials performed a broad range of research concerned with synthesizing, characterizing and utilizing atomic and molecular clusters, nanoparticles and nanomaterial...

  8. A Multidimensional and Multimembership Clustering Method for Social Networks and Its Application in Customer Relationship Management

    Directory of Open Access Journals (Sweden)

    Peixin Zhao

    2013-01-01

    Full Text Available Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

  9. Quality Control Guidelines for SAM Chemical Methods

    Science.gov (United States)

    Learn more about quality control guidelines and recommendations for the analysis of samples using the chemistry methods listed in EPA's Selected Analytical Methods for Environmental Remediation and Recovery (SAM).

  10. Trend analysis using non-stationary time series clustering based on the finite element method

    OpenAIRE

    Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.

    2014-01-01

    In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...

  11. Potential for supernova-induced chemical enrichment of protoglobular cluster clouds

    International Nuclear Information System (INIS)

    Dopita, M.A.; Smith, G.H.; Dominion Astrophysical Observatory, Victoria, Canada)

    1986-01-01

    This paper seeks to explain the large internal abundance variations that are seen in the globular cluster Omega Cen in terms of supernova-induced chemical enrichment that occurred when the cluster was still largely in a gaseous phase and star formation was continuing. Using a simple power-law density model of this protoglobular gas cloud, the conditions under which this can occur have been established analytically. Clouds less massive than about 100,000 solar masses are completely disrupted by supernova explosions in their adiabatic phase. In clouds of greater mass, supernova explosions occurring near the tidal radius tend to lose their hot gas and metals to the intercloud medium. For explosions occurring closer to the mass center the ejecta must be slowed below the escape velocity, and this can only occur in clouds more massive than about 3 x 10 to the 6th solar masses. If this condition is met, then the slow isothermal momentum-conserving shocks generated by the supernova explosions may eventually induce secondary star formation. For such shocks converging on the mass center, it is found that a cloud mass of at least 10 to the 7th solar masses is required for this process to be efficient. From the observed properties of Omega Cen, a primordial mass of order 10 to the 8th solar masses is estimated, which emphasizes the unusual character of this object. 39 references

  12. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine.

    Science.gov (United States)

    Lei, Yang; Yu, Dai; Bin, Zhang; Yang, Yang

    2017-01-01

    Clustering algorithm as a basis of data analysis is widely used in analysis systems. However, as for the high dimensions of the data, the clustering algorithm may overlook the business relation between these dimensions especially in the medical fields. As a result, usually the clustering result may not meet the business goals of the users. Then, in the clustering process, if it can combine the knowledge of the users, that is, the doctor's knowledge or the analysis intent, the clustering result can be more satisfied. In this paper, we propose an interactive K -means clustering method to improve the user's satisfactions towards the result. The core of this method is to get the user's feedback of the clustering result, to optimize the clustering result. Then, a particle swarm optimization algorithm is used in the method to optimize the parameters, especially the weight settings in the clustering algorithm to make it reflect the user's business preference as possible. After that, based on the parameter optimization and adjustment, the clustering result can be closer to the user's requirement. Finally, we take an example in the breast cancer, to testify our method. The experiments show the better performance of our algorithm.

  13. A Chemical Composition Survey of the Iron-complex Globular Cluster NGC 6273 (M19)

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, Christian I.; Caldwell, Nelson [Harvard–Smithsonian Center for Astrophysics, 60 Garden Street, MS-15, Cambridge, MA 02138 (United States); Rich, R. Michael [Department of Physics and Astronomy, UCLA, 430 Portola Plaza, Box 951547, Los Angeles, CA 90095-1547 (United States); Mateo, Mario [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Bailey, John I. III [Leiden Observatory, Leiden University, P.O. Box 9513, 2300RA Leiden (Netherlands); Clarkson, William I. [Department of Natural Sciences, University of Michigan–Dearborn, 4901 Evergreen Road, Dearborn, MI 48128 (United States); Olszewski, Edward W. [Steward Observatory, The University of Arizona, 933 N. Cherry Avenue, Tucson, AZ 85721 (United States); Walker, Matthew G., E-mail: cjohnson@cfa.harvard.edu, E-mail: ncaldwell@cfa.harvard.edu, E-mail: rmr@astro.ucla.edu, E-mail: mmateo@umich.edu, E-mail: baileyji@strw.leidenuniv.nl, E-mail: wiclarks@umich.edu, E-mail: eolszewski@as.arizona.edu, E-mail: mgwalker@andrew.cmu.edu [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

    2017-02-20

    Recent observations have shown that a growing number of the most massive Galactic globular clusters contain multiple populations of stars with different [Fe/H] and neutron-capture element abundances. NGC 6273 has only recently been recognized as a member of this “iron-complex” cluster class, and we provide here a chemical and kinematic analysis of >300 red giant branch and asymptotic giant branch member stars using high-resolution spectra obtained with the Magellan –M2FS and VLT–FLAMES instruments. Multiple lines of evidence indicate that NGC 6273 possesses an intrinsic metallicity spread that ranges from about [Fe/H] = −2 to −1 dex, and may include at least three populations with different [Fe/H] values. The three populations identified here contain separate first (Na/Al-poor) and second (Na/Al-rich) generation stars, but a Mg–Al anti-correlation may only be present in stars with [Fe/H] ≳ −1.65. The strong correlation between [La/Eu] and [Fe/H] suggests that the s-process must have dominated the heavy element enrichment at higher metallicities. A small group of stars with low [ α /Fe] is identified and may have been accreted from a former surrounding field star population. The cluster’s large abundance variations are coupled with a complex, extended, and multimodal blue horizontal branch (HB). The HB morphology and chemical abundances suggest that NGC 6273 may have an origin that is similar to ω Cen and M54.

  14. Field theoretical methods in chemical physics

    International Nuclear Information System (INIS)

    Paul, R.

    1982-01-01

    Field theory will become an important tool for the chemist, and this book presents a clear and thorough account of the theory itself and its applications for solving a wide variety of chemical problems. The author has brought together the foundations upon which the many and varied applications of field theory have been built, giving more intermediate steps than is usual in the derivations. This makes the book easily accessible to anyone with a background of calculus, statistical thermodynamics and elementary quantum chemistry. (orig./HK)

  15. The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Detailed Age and Abundance Gradients using DR12

    Science.gov (United States)

    Frinchaboy, Peter M.; Thompson, Benjamin A.; O'Connell, Julia; Meyer, Brianne; Donor, John; Majewski, Steven R.; Holtzman, Jon A.; Zasowski, Gail; Beers, Timothy C.; Beaton, Rachael; Cunha, Katia M. L.; Hearty, Fred; Nidever, David L.; Schiavon, Ricardo P.; Smith, Verne V.; Hayden, Michael R.

    2015-01-01

    We present detailed abundance results for Galactic open clusters as part of the Open Cluster Chemical Abundances and Mapping (OCCAM) Survey, which is based primarily on data from the Sloan Digital Sky Survey/ Apache Point Observatory Galactic Evolution Experiment. Using 100 open clusters from the uniformly observed complete SDSS-III/APOGEE-1 DR12 dataset, we present age and multi-element abundance gradients for the disk of the Milky Way.This work is supported by an NSF AAG grant AST-1311835.

  16. Anharmonic effects in the quantum cluster equilibrium method

    Science.gov (United States)

    von Domaros, Michael; Perlt, Eva

    2017-03-01

    The well-established quantum cluster equilibrium (QCE) model provides a statistical thermodynamic framework to apply high-level ab initio calculations of finite cluster structures to macroscopic liquid phases using the partition function. So far, the harmonic approximation has been applied throughout the calculations. In this article, we apply an important correction in the evaluation of the one-particle partition function and account for anharmonicity. Therefore, we implemented an analytical approximation to the Morse partition function and the derivatives of its logarithm with respect to temperature, which are required for the evaluation of thermodynamic quantities. This anharmonic QCE approach has been applied to liquid hydrogen chloride and cluster distributions, and the molar volume, the volumetric thermal expansion coefficient, and the isobaric heat capacity have been calculated. An improved description for all properties is observed if anharmonic effects are considered.

  17. A crystalline cluster method for deep impurities in insulators

    International Nuclear Information System (INIS)

    Guimaraes, P.S.

    1983-01-01

    An 'ab initio' self-consistent-field crystalline-cluster approach to the study of deep impurity states in insulators is proposed. It is shown that, in spite of being a cluster calculation, the interaction of the impurity with the crystal environment is fully taken into account. It is also shown that the present representation of the impurity states is, at least, as precise as the crystalline cluster representation of the pure crystal electronic structure. The procedure has been tested by performing the calculation of the electronic structure of the U center in a sodium chloride crystal, and it has been observed that the calculated GAMMA 1 - GAMMA 15 absorption energy is in good agreement with experiment. (Author) [pt

  18. A crystalline cluster method for deep impurities in insulators

    International Nuclear Information System (INIS)

    Guimaraes, P.S.

    1983-01-01

    An ''ab initio'' self-consistent-field crysttalline-cluster approach to the study of deep impurity states in insulators is proposed. It is shown that, in spite of being a cluster calculation, the interaction of the impurity with the crystal environment is fully taken into account. It is also shown that the present representation of the impurity states is, at least, as precise as the crystalline cluster representation of the pure crystal electronic structure. The procedure has been tested by performing the calculation of the electronic structure of the U center in a sodium chloride crystal, and it has been observed that the calculated γ 1 - γ 15 absorption energy is in good agreement with experiment. (author) [pt

  19. Chemical decontamination method in nuclear facility system

    International Nuclear Information System (INIS)

    Takahashi, Ryota; Sakai, Hitoshi; Oka, Shigehiro.

    1996-01-01

    Pumps and valves in a closed recycling loop system incorporating materials to be chemically decontaminated are decomposed, a guide plate having the decomposed parts as an exit/inlet of a decontaminating liquid is formed, and a decontaminating liquid recycling loop comprising a recycling pump and a heater is connected to the guide plate. Decontaminating liquid from a decontaminating liquid storage tank is supplied to the decontaminating liquid recycling loop. With such constitutions, the decontaminating liquid is filled in the recycling closed loop system incorporating materials to be decontaminated, and the materials to be decontaminated are chemically decontaminated. The decontaminating liquid after the decontamination is discharged and flows, if necessary, in a recycling system channel for repeating supply and discharge. After the decontamination, the guide plate is removed and returned to the original recycling loop. When pipelines of a reactor recycling system are decontaminated, the amount of decontaminations can be decreased, and reforming construction for assembling the recycling loop again, which requires cutting for pipelines in the system is no more necessary. Accordingly, the amount of wastes can be decreased, and therefore, the decontamination operation is facilitated and radiation dose can be reduced. (T.M.)

  20. Method for discovering relationships in data by dynamic quantum clustering

    Science.gov (United States)

    Weinstein, Marvin; Horn, David

    2014-10-28

    Data clustering is provided according to a dynamical framework based on quantum mechanical time evolution of states corresponding to data points. To expedite computations, we can approximate the time-dependent Hamiltonian formalism by a truncated calculation within a set of Gaussian wave-functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states, opening up the possibility of exploration of relationships among data-points through observation of varying dynamical-distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing, such as dimensional reduction through singular value decomposition and/or feature filtering.

  1. A dynamic lattice searching method with rotation operation for optimization of large clusters

    International Nuclear Information System (INIS)

    Wu Xia; Cai Wensheng; Shao Xueguang

    2009-01-01

    Global optimization of large clusters has been a difficult task, though much effort has been paid and many efficient methods have been proposed. During our works, a rotation operation (RO) is designed to realize the structural transformation from decahedra to icosahedra for the optimization of large clusters, by rotating the atoms below the center atom with a definite degree around the fivefold axis. Based on the RO, a development of the previous dynamic lattice searching with constructed core (DLSc), named as DLSc-RO, is presented. With an investigation of the method for the optimization of Lennard-Jones (LJ) clusters, i.e., LJ 500 , LJ 561 , LJ 600 , LJ 665-667 , LJ 670 , LJ 685 , and LJ 923 , Morse clusters, silver clusters by Gupta potential, and aluminum clusters by NP-B potential, it was found that both the global minima with icosahedral and decahedral motifs can be obtained, and the method is proved to be efficient and universal.

  2. Solvation effects on chemical shifts by embedded cluster integral equation theory.

    Science.gov (United States)

    Frach, Roland; Kast, Stefan M

    2014-12-11

    The accurate computational prediction of nuclear magnetic resonance (NMR) parameters like chemical shifts represents a challenge if the species studied is immersed in strongly polarizing environments such as water. Common approaches to treating a solvent in the form of, e.g., the polarizable continuum model (PCM) ignore strong directional interactions such as H-bonds to the solvent which can have substantial impact on magnetic shieldings. We here present a computational methodology that accounts for atomic-level solvent effects on NMR parameters by extending the embedded cluster reference interaction site model (EC-RISM) integral equation theory to the prediction of chemical shifts of N-methylacetamide (NMA) in aqueous solution. We examine the influence of various so-called closure approximations of the underlying three-dimensional RISM theory as well as the impact of basis set size and different treatment of electrostatic solute-solvent interactions. We find considerable and systematic improvement over reference PCM and gas phase calculations. A smaller basis set in combination with a simple point charge model already yields good performance which can be further improved by employing exact electrostatic quantum-mechanical solute-solvent interaction energies. A larger basis set benefits more significantly from exact over point charge electrostatics, which can be related to differences of the solvent's charge distribution.

  3. Chemical decontamination method for radioactive metal waste

    International Nuclear Information System (INIS)

    Onuma, Tsutomu; Tanaka, Akio; Shibuya, Sadao.

    1991-01-01

    When contaminants mainly composed of copper remained on the surface of stainless steel wastes sent from an electrolytic reduction as a first step are chemically decontaminated, metal wastes are discriminated to carbon steel wastes and stainless steel wastes. Then, the carbon steel wastes are applied only with the first step of immersing in a sulfuric acid solution, and stainless steel wastes are applied with a first step of immersing into a sulfuric acid solution for electrolytic reduction for a predetermined period of time and a second step of immersing into a liquid in which an oxidative metal salt is added to sulfuric acid. The decontamination liquid which is used for immersing the stainless steel wastes in the second step and the oxidation force of which is lowered is used as the sulfuric acid solution in the first step for the carbon steel wastes. In view of the above, the decontamination liquid of the second step can be utilized most effectively, enabling to greatly decrease the secondary wastes and to improve decontamination efficiency. (T.M.)

  4. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

    Directory of Open Access Journals (Sweden)

    Huanhuan Li

    2017-08-01

    Full Text Available The Shipboard Automatic Identification System (AIS is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW, a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our

  5. A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis.

    Science.gov (United States)

    Li, Huanhuan; Liu, Jingxian; Liu, Ryan Wen; Xiong, Naixue; Wu, Kefeng; Kim, Tai-Hoon

    2017-08-04

    The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

  6. A cluster merging method for time series microarray with production values.

    Science.gov (United States)

    Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio

    2014-09-01

    A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.

  7. Consensus of satellite cluster flight using an energy-matching optimal control method

    Science.gov (United States)

    Luo, Jianjun; Zhou, Liang; Zhang, Bo

    2017-11-01

    This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

  8. An Extended Affinity Propagation Clustering Method Based on Different Data Density Types

    Directory of Open Access Journals (Sweden)

    XiuLi Zhao

    2015-01-01

    Full Text Available Affinity propagation (AP algorithm, as a novel clustering method, does not require the users to specify the initial cluster centers in advance, which regards all data points as potential exemplars (cluster centers equally and groups the clusters totally by the similar degree among the data points. But in many cases there exist some different intensive areas within the same data set, which means that the data set does not distribute homogeneously. In such situation the AP algorithm cannot group the data points into ideal clusters. In this paper, we proposed an extended AP clustering algorithm to deal with such a problem. There are two steps in our method: firstly the data set is partitioned into several data density types according to the nearest distances of each data point; and then the AP clustering method is, respectively, used to group the data points into clusters in each data density type. Two experiments are carried out to evaluate the performance of our algorithm: one utilizes an artificial data set and the other uses a real seismic data set. The experiment results show that groups are obtained more accurately by our algorithm than OPTICS and AP clustering algorithm itself.

  9. Investigation of Evaluation method of chemical runaway reaction

    International Nuclear Information System (INIS)

    Sato, Yoshihiko; Sasaya, Shinji; Kurakata, Koichiro; Nojiri, Ichiro

    2002-02-01

    Safety study 'Study of evaluation of abnormal occurrence for chemical substances in the nuclear fuel facilities' will be carried out from 2001 to 2005. In this study, the prediction of thermal hazards of chemical substances will be investigated and prepared. The hazard prediction method of chemical substances will be constructed from these results. Therefore, the hazard prediction methods applied in the chemical engineering in which the chemical substances with the hazard of fire and explosion were often treated were investigated. CHETAH (The ASTM Computer Program for Chemical Thermodynamic and Energy Release Evaluation) developed by ASTM (American Society for Testing and Materials) and TSS (Thermal Safety Software) developed by CISP (ChemInform St. Petersburg) were introduced and the fire and explosion hazards of chemical substances and reactions in the reprocessing process were evaluated. From these evaluated results, CHETAH could almost estimate the heat of reaction at 10% accuracy. It was supposed that CHETAH was useful as a screening for the hazards of fire and explosion of the new chemical substances and so on. TSS could calculate the reaction rate and the reaction behavior from the data measured by the various calorimeters rapidly. It was supposed that TSS was useful as an evaluation method for the hazards of fire and explosion of the new chemical reactions and so on. (author)

  10. Chemical Compounds and Extraction Methods of ?Maollahm?

    OpenAIRE

    Sadeghpoor, Omid; Dayeni, Manijeh; Razi, Samane

    2016-01-01

    Background: Maollahm or meat juice, a by-product of meat, is a traditional remedy in Persian medicine. This product was used as a nourishment or treatment substance for sick people. According to the ancient Persian medicine, animal meat has more affinity with the human body and the body easily absorbs its nutrition. Therefore, one could resort to maollahm for patients requiring urgent nourishment to boost and strengthen their body. Methods: In this work, different ways of preparing maollahm f...

  11. A NEW METHOD TO QUANTIFY X-RAY SUBSTRUCTURES IN CLUSTERS OF GALAXIES

    Energy Technology Data Exchange (ETDEWEB)

    Andrade-Santos, Felipe; Lima Neto, Gastao B.; Lagana, Tatiana F. [Departamento de Astronomia, Instituto de Astronomia, Geofisica e Ciencias Atmosfericas, Universidade de Sao Paulo, Geofisica e Ciencias Atmosfericas, Rua do Matao 1226, Cidade Universitaria, 05508-090 Sao Paulo, SP (Brazil)

    2012-02-20

    We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model ({beta}-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z in [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high- and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high- and low-substructure level clusters) are different (they present an offset, i.e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

  12. Investigation of Chemical Equilibrium Kinetics by the Electromigration Method

    CERN Document Server

    Bozhikov, G A; Bontchev, G D; Maslov, O D; Milanov, M V; Dmitriev, S N

    2002-01-01

    Measurement of the chemical reaction rates for complex formation as well as hydrolysis type reactions by the method of horizontal zone electrophoresis is outlined. The correlation between chemical equilibrium kinetics and electrodiffusion processes in a constant d.c. electric field is described. In model electromigration experiments the reaction rate constant of the complex formation of Hf(IV) and DTPA is determined.

  13. CHEMICAL COMPOSITION OF INTERMEDIATE-MASS STAR MEMBERS OF THE M6 (NGC 6405) OPEN CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Kılıçoğlu, T.; Albayrak, B. [Ankara University, Faculty of Science, Department of Astronomy and Space Sciences, 06100, Tandoğan, Ankara (Turkey); Monier, R. [LESIA, UMR 8109, Observatoire de Paris Meudon, Place J. Janssen, Meudon (France); Richer, J. [Département de physique, Université de Montréal, 2900, Boulevard Edouard-Montpetit, Montréal QC, H3C 3J7 (Canada); Fossati, L., E-mail: tkilicoglu@ankara.edu.tr, E-mail: balbayrak@ankara.edu.tr, E-mail: Richard.Monier@obspm.fr, E-mail: Jacques.Richer@umontreal.ca, E-mail: lfossati@astro.uni-bonn.de [Argelander-Institut für Astronomie der Universität Bonn, Auf dem Hügel 71, D-53121, Bonn (Germany)

    2016-03-15

    We present here the first abundance analysis of 44 late B-, A-, and F-type members of the young open cluster M6 (NGC 6405, age about 75 Myr). Low- and medium-resolution spectra, covering the 4500–5840 Å wavelength range, were obtained using the FLAMES/GIRAFFE spectrograph attached to the ESO Very Large Telescopes. We determined the atmospheric parameters using calibrations of the Geneva photometry and by adjusting the H{sub β} profiles to synthetic ones. The abundances of up to 20 chemical elements, from helium to mercury, were derived for 19 late B, 16 A, and 9 F stars by iteratively adjusting synthetic spectra to the observations. We also derived a mean cluster metallicity of [Fe/H] = 0.07 ± 0.03 dex from the iron abundances of the F-type stars. We find that for most chemical elements, the normal late B- and A-type stars exhibit larger star-to-star abundance variations than the F-type stars probably because of the faster rotation of the B and A stars. The abundances of C, O, Mg, Si, and Sc appear to be anticorrelated with that of Fe, while the opposite holds for the abundances of Ca, Ti, Cr, Mn, Ni, Y, and Ba as expected if radiative diffusion is efficient in the envelopes of these stars. In the course of this analysis, we discovered five new peculiar stars: one mild Am, one Am, and one Fm star (HD 318091, CD-32 13109, GSC 07380-01211, CP1), one HgMn star (HD 318126, CP3), and one He-weak P-rich (HD 318101, CP4) star. We also discovered a new spectroscopic binary, most likely a SB2. We performed a detailed modeling of HD 318101, the new He-weak P-rich CP star, using the Montréal stellar evolution code XEVOL which self-consistently treats all particle transport processes. Although the overall abundance pattern of this star is properly reproduced, we find that detailed abundances (in particular the high P excess) resisted modeling attempts even when a range of turbulence profiles and mass-loss rates were considered. Solutions are proposed which are

  14. Investigation of the cluster formation in lithium niobate crystals by computer modeling method

    Energy Technology Data Exchange (ETDEWEB)

    Voskresenskii, V. M.; Starodub, O. R., E-mail: ol-star@mail.ru; Sidorov, N. V.; Palatnikov, M. N. [Russian Academy of Sciences, Tananaev Institute of Chemistry and Technology of Rare Earth Elements and Mineral Raw Materials, Kola Science Centre (Russian Federation)

    2017-03-15

    The processes occurring upon the formation of energetically equilibrium oxygen-octahedral clusters in the ferroelectric phase of a stoichiometric lithium niobate (LiNbO{sub 3}) crystal have been investigated by the computer modeling method within the semiclassical atomistic model. An energetically favorable cluster size (at which a structure similar to that of a congruent crystal is organized) is shown to exist. A stoichiometric cluster cannot exist because of the electroneutrality loss. The most energetically favorable cluster is that with a Li/Nb ratio of about 0.945, a value close to the lithium-to-niobium ratio for a congruent crystal.

  15. Method of cleaning oil slicks and chemical spills

    International Nuclear Information System (INIS)

    Billings, L.

    1992-01-01

    This patent describes a method of cleaning a floating chemical spill on a body of water. It comprises: providing a quantity of popular bark-based pelleted or granular product, flotation means and a flexible net having openings generally smaller than the smallest whole pellet dimension of the pelleted product, spreading the net over a chemical spill on the body of water, connecting the floatation means to the net thereby supporting the net adjacent the surface of the body of water, placing the poplar bark-based product on the net, absorbing the floating chemical spill into the product, and removing the chemical soaked product from the body of water

  16. Clustering Methods; Part IV of Scientific Report No. ISR-18, Information Storage and Retrieval...

    Science.gov (United States)

    Cornell Univ., Ithaca, NY. Dept. of Computer Science.

    Two papers are included as Part Four of this report on Salton's Magical Automatic Retriever of Texts (SMART) project report. The first paper: "A Controlled Single Pass Classification Algorithm with Application to Multilevel Clustering" by D. B. Johnson and J. M. Laferente presents a single pass clustering method which compares favorably…

  17. An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

    Science.gov (United States)

    Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

    2013-05-01

    Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

  18. Performance Analysis of Entropy Methods on K Means in Clustering Process

    Science.gov (United States)

    Dicky Syahputra Lubis, Mhd.; Mawengkang, Herman; Suwilo, Saib

    2017-12-01

    K Means is a non-hierarchical data clustering method that attempts to partition existing data into one or more clusters / groups. This method partitions the data into clusters / groups so that data that have the same characteristics are grouped into the same cluster and data that have different characteristics are grouped into other groups.The purpose of this data clustering is to minimize the objective function set in the clustering process, which generally attempts to minimize variation within a cluster and maximize the variation between clusters. However, the main disadvantage of this method is that the number k is often not known before. Furthermore, a randomly chosen starting point may cause two points to approach the distance to be determined as two centroids. Therefore, for the determination of the starting point in K Means used entropy method where this method is a method that can be used to determine a weight and take a decision from a set of alternatives. Entropy is able to investigate the harmony in discrimination among a multitude of data sets. Using Entropy criteria with the highest value variations will get the highest weight. Given this entropy method can help K Means work process in determining the starting point which is usually determined at random. Thus the process of clustering on K Means can be more quickly known by helping the entropy method where the iteration process is faster than the K Means Standard process. Where the postoperative patient dataset of the UCI Repository Machine Learning used and using only 12 data as an example of its calculations is obtained by entropy method only with 2 times iteration can get the desired end result.

  19. PARTIAL TRAINING METHOD FOR HEURISTIC ALGORITHM OF POSSIBLE CLUSTERIZATION UNDER UNKNOWN NUMBER OF CLASSES

    Directory of Open Access Journals (Sweden)

    D. A. Viattchenin

    2009-01-01

    Full Text Available A method for constructing a subset of labeled objects which is used in a heuristic algorithm of possible  clusterization with partial  training is proposed in the  paper.  The  method  is  based  on  data preprocessing by the heuristic algorithm of possible clusterization using a transitive closure of a fuzzy tolerance. Method efficiency is demonstrated by way of an illustrative example.

  20. Variational methods for chemical and nuclear reactions

    International Nuclear Information System (INIS)

    Crawford, O.H.

    1977-01-01

    All the variational functionals are derived which satisfy certain criteria of suitability for molecular and nuclear scattering, below the threshold energy for three-body breakup. The existence and uniqueness of solutions are proven. The most general suitable functional is specialized, by particular values of its parameters, to Kohn's taneta, Kato's cot(eta-theta), the inverse Kohn coeta, Kohn's S matrix, our S matrix, Lane and Robson's functional, and several new functionals, an infinite number of which are contained in the general expression. Four general ways of deriving algebraic methods from a given functional are discussed, and illustrated with specific algebraic results. These include equations of Lane and Robson and of Kohn, the fundamental R matrix relation, and new equations. The relative configuration space is divided as in the Wigner R matrix theory, and trial wavefunctions are needed for only the region where all the particles are interacting. In addition, a version of the general functional is presented which does not require any division of space

  1. A two-stage method for microcalcification cluster segmentation in mammography by deformable models

    International Nuclear Information System (INIS)

    Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.; Karahaliou, A.; Costaridou, L.; Vassiou, K.

    2015-01-01

    Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods are applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST cluster , average of minimum distance—AMINDIST cluster ) and the area overlap measure (AOM cluster ). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross

  2. Odour detection methods: olfactometry and chemical sensors.

    Science.gov (United States)

    Brattoli, Magda; de Gennaro, Gianluigi; de Pinto, Valentina; Loiotile, Annamaria Demarinis; Lovascio, Sara; Penza, Michele

    2011-01-01

    The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc.) and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality); this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants) as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective "analytical instrument" for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses) are then described, focusing on their better performances for environmental analysis. Odour emission monitoring carried out through

  3. Odour Detection Methods: Olfactometry and Chemical Sensors

    Directory of Open Access Journals (Sweden)

    Sara Lovascio

    2011-05-01

    Full Text Available The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc. and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality; this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective “analytical instrument” for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses are then described, focusing on their better performances for environmental analysis. Odour emission monitoring

  4. The swift UVOT stars survey. I. Methods and test clusters

    Energy Technology Data Exchange (ETDEWEB)

    Siegel, Michael H.; Porterfield, Blair L.; Linevsky, Jacquelyn S.; Bond, Howard E.; Hoversten, Erik A.; Berrier, Joshua L.; Gronwall, Caryl A. [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802 (United States); Holland, Stephen T. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Breeveld, Alice A. [Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey RH5 6NT (United Kingdom); Brown, Peter J., E-mail: siegel@astro.psu.edu, E-mail: blp14@psu.edu, E-mail: heb11@psu.edu, E-mail: caryl@astro.psu.edu, E-mail: sholland@stsci.edu, E-mail: aab@mssl.ucl.ac.uk, E-mail: grbpeter@yahoo.com [George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Texas A. and M. University, Department of Physics and Astronomy, 4242 TAMU, College Station, TX 77843 (United States)

    2014-12-01

    We describe the motivations and background of a large survey of nearby stellar populations using the Ultraviolet Optical Telescope (UVOT) on board the Swift Gamma-Ray Burst Mission. UVOT, with its wide field, near-UV sensitivity, and 2.″3 spatial resolution, is uniquely suited to studying nearby stellar populations and providing insight into the near-UV properties of hot stars and the contribution of those stars to the integrated light of more distant stellar populations. We review the state of UV stellar photometry, outline the survey, and address problems specific to wide- and crowded-field UVOT photometry. We present color–magnitude diagrams of the nearby open clusters M67, NGC 188, and NGC 2539, and the globular cluster M79. We demonstrate that UVOT can easily discern the young- and intermediate-age main sequences, blue stragglers, and hot white dwarfs, producing results consistent with previous studies. We also find that it characterizes the blue horizontal branch of M79 and easily identifies a known post-asymptotic giant branch star.

  5. The swift UVOT stars survey. I. Methods and test clusters

    International Nuclear Information System (INIS)

    Siegel, Michael H.; Porterfield, Blair L.; Linevsky, Jacquelyn S.; Bond, Howard E.; Hoversten, Erik A.; Berrier, Joshua L.; Gronwall, Caryl A.; Holland, Stephen T.; Breeveld, Alice A.; Brown, Peter J.

    2014-01-01

    We describe the motivations and background of a large survey of nearby stellar populations using the Ultraviolet Optical Telescope (UVOT) on board the Swift Gamma-Ray Burst Mission. UVOT, with its wide field, near-UV sensitivity, and 2.″3 spatial resolution, is uniquely suited to studying nearby stellar populations and providing insight into the near-UV properties of hot stars and the contribution of those stars to the integrated light of more distant stellar populations. We review the state of UV stellar photometry, outline the survey, and address problems specific to wide- and crowded-field UVOT photometry. We present color–magnitude diagrams of the nearby open clusters M67, NGC 188, and NGC 2539, and the globular cluster M79. We demonstrate that UVOT can easily discern the young- and intermediate-age main sequences, blue stragglers, and hot white dwarfs, producing results consistent with previous studies. We also find that it characterizes the blue horizontal branch of M79 and easily identifies a known post-asymptotic giant branch star.

  6. Safety in the Chemical Laboratory--Chemical Management: A Method for Waste Reduction.

    Science.gov (United States)

    Pine, Stanley H.

    1984-01-01

    Discusses methods for reducing or eliminating waste disposal problems in the chemistry laboratory, considering both economic and environmental aspects of the problems. Proposes inventory control, shared use, solvent recycling, zero effluent, and various means of disposing of chemicals. (JM)

  7. Fast optimization of binary clusters using a novel dynamic lattice searching method

    International Nuclear Information System (INIS)

    Wu, Xia; Cheng, Wen

    2014-01-01

    Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd) 79 clusters with DFT-fit parameters of Gupta potential

  8. Measuring age differences among globular clusters having similar metallicities - A new method and first results

    International Nuclear Information System (INIS)

    Vandenberg, D.A.; Bolte, M.; Stetson, P.B.

    1990-01-01

    A color-difference technique for estimating the relative ages of globular clusters with similar chemical compositions on the basis of their CM diagrams is described and demonstrated. The theoretical basis and implementation of the procedure are explained, and results for groups of globular clusters with m/H = about -2, -1.6, and -1.3, and for two special cases (Palomar 12 and NGC 5139) are presented in extensive tables and graphs and discussed in detail. It is found that the more metal-deficient globular clusters are nearly coeval (differences less than 0.5 Gyr), whereas the most metal-rich globular clusters exhibit significant age differences (about 2 Gyr). This result is shown to contradict Galactic evolution models postulating halo collapse in less than a few times 100 Myr. 77 refs

  9. Heuristic methods using grasp, path relinking and variable neighborhood search for the clustered traveling salesman problem

    Directory of Open Access Journals (Sweden)

    Mário Mestria

    2013-08-01

    Full Text Available The Clustered Traveling Salesman Problem (CTSP is a generalization of the Traveling Salesman Problem (TSP in which the set of vertices is partitioned into disjoint clusters and objective is to find a minimum cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously. The CTSP is NP-hard and, in this context, we are proposed heuristic methods for the CTSP using GRASP, Path Relinking and Variable Neighborhood Descent (VND. The heuristic methods were tested using Euclidean instances with up to 2000 vertices and clusters varying between 4 to 150 vertices. The computational tests were performed to compare the performance of the heuristic methods with an exact algorithm using the Parallel CPLEX software. The computational results showed that the hybrid heuristic method using VND outperforms other heuristic methods.

  10. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang

    2017-02-16

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  11. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

    2017-01-01

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  12. Assessing the sensitivity of benzene cluster cation chemical ionization mass spectrometry toward a wide array of biogenic volatile organic compounds

    Science.gov (United States)

    Lavi, Avi; Vermeuel, Michael; Novak, Gordon; Bertram, Timothy

    2017-04-01

    Chemical ionization mass spectrometry is a real-time, sensitive and selective measurement technique for the detection of volatile organic compounds (VOCs). The benefits of CIMS technology make it highly suitable for field measurements that requires fast (10Hz and higher) response rates, such as the study of surface-atmosphere exchange processes by the eddy covariance method. The use of benzene cluster cations as a regent ion was previously demonstrated as a sensitive and selective method for the detection of select biogenic VOCs (e.g. isoprene, monoterpenes and sesquiterpenes) [Kim et al., 2016; Leibrock and Huey, 2000]. Quantitative analysis of atmospheric trace gases necessitates calibration for each analyte as a function of atmospheric conditions. We describe a custom designed calibration system, based on liquid evaporation, for determination of the sensitivity of the benzene-CIMS to a wide range of organic compounds at atmospherically relevant mixing ratios (volatile organic compounds, Atmos Meas Tech, 9(4), 1473-1484, doi:10.5194/amt-9-1473-2016. Leibrock, E., and L. G. Huey (2000), Ion chemistry for the detection of isoprene and other volatile organic compounds in ambient air, Geophys Res Lett, 27(12), 1719-1722, doi:Doi 10.1029/1999gl010804.

  13. Calculation of Multiphase Chemical Equilibrium by the Modified RAND Method

    DEFF Research Database (Denmark)

    Tsanas, Christos; Stenby, Erling Halfdan; Yan, Wei

    2017-01-01

    method. The modified RAND extends the classical RAND method from single-phase chemical reaction equilibrium of ideal systems to multiphase chemical equilibrium of nonideal systems. All components in all phases are treated in the same manner and the system Gibbs energy can be used to monitor convergence....... This is the first time that modified RAND was applied to multiphase chemical equilibrium systems. The combined algorithm was tested using nine examples covering vapor–liquid (VLE) and vapor–liquid–liquid equilibria (VLLE) of ideal and nonideal reaction systems. Successive substitution provided good initial......A robust and efficient algorithm for simultaneous chemical and phase equilibrium calculations is proposed. It combines two individual nonstoichiometric solving procedures: a nested-loop method with successive substitution for the first steps and final convergence with the second-order modified RAND...

  14. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods.

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community.

  15. Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods

    Science.gov (United States)

    Šubelj, Lovro; van Eck, Nees Jan; Waltman, Ludo

    2016-01-01

    Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network. In the network science literature, many clustering methods, often referred to as graph partitioning or community detection techniques, have been developed. Focusing on the problem of clustering the publications in a citation network, we present a systematic comparison of the performance of a large number of these clustering methods. Using a number of different citation networks, some of them relatively small and others very large, we extensively study the statistical properties of the results provided by different methods. In addition, we also carry out an expert-based assessment of the results produced by different methods. The expert-based assessment focuses on publications in the field of scientometrics. Our findings seem to indicate that there is a trade-off between different properties that may be considered desirable for a good clustering of publications. Overall, map equation methods appear to perform best in our analysis, suggesting that these methods deserve more attention from the bibliometric community. PMID:27124610

  16. Chemical analysis of cyanide in cyanidation process: review of methods

    International Nuclear Information System (INIS)

    Nova-Alonso, F.; Elorza-Rodriguez, E.; Uribe-Salas, A.; Perez-Garibay, R.

    2007-01-01

    Cyanidation, the world wide method for precious metals recovery, the chemical analysis of cyanide, is a very important, but complex operation. Cyanide can be present forming different species, each of them with different stability, toxicity, analysis method and elimination technique. For cyanide analysis, there exists a wide selection of analytical methods but most of them present difficulties because of the interference of species present in the solution. This paper presents the different available methods for chemical analysis of cyanide: titration, specific electrode and distillation, giving special emphasis on the interferences problem, with the aim of helping in the interpretation of the results. (Author)

  17. Cluster cosmological analysis with X ray instrumental observables: introduction and testing of AsPIX method

    International Nuclear Information System (INIS)

    Valotti, Andrea

    2016-01-01

    Cosmology is one of the fundamental pillars of astrophysics, as such it contains many unsolved puzzles. To investigate some of those puzzles, we analyze X-ray surveys of galaxy clusters. These surveys are possible thanks to the bremsstrahlung emission of the intra-cluster medium. The simultaneous fit of cluster counts as a function of mass and distance provides an independent measure of cosmological parameters such as Ω m , σ s , and the dark energy equation of state w0. A novel approach to cosmological analysis using galaxy cluster data, called top-down, was developed in N. Clerc et al. (2012). This top-down approach is based purely on instrumental observables that are considered in a two-dimensional X-ray color-magnitude diagram. The method self-consistently includes selection effects and scaling relationships. It also provides a means of bypassing the computation of individual cluster masses. My work presents an extension of the top-down method by introducing the apparent size of the cluster, creating a three-dimensional X-ray cluster diagram. The size of a cluster is sensitive to both the cluster mass and its angular diameter, so it must also be included in the assessment of selection effects. The performance of this new method is investigated using a Fisher analysis. In parallel, I have studied the effects of the intrinsic scatter in the cluster size scaling relation on the sample selection as well as on the obtained cosmological parameters. To validate the method, I estimate uncertainties of cosmological parameters with MCMC method Amoeba minimization routine and using two simulated XMM surveys that have an increasing level of complexity. The first simulated survey is a set of toy catalogues of 100 and 10000 deg 2 , whereas the second is a 1000 deg 2 catalogue that was generated using an Aardvark semi-analytical N-body simulation. This comparison corroborates the conclusions of the Fisher analysis. In conclusion, I find that a cluster diagram that accounts

  18. Chemical compositions, methods of making the chemical compositions, and structures made from the chemical compositions

    Science.gov (United States)

    Yang, Lei; Cheng, Zhe; Liu, Ze; Liu, Meilin

    2015-01-13

    Embodiments of the present disclosure include chemical compositions, structures, anodes, cathodes, electrolytes for solid oxide fuel cells, solid oxide fuel cells, fuel cells, fuel cell membranes, separation membranes, catalytic membranes, sensors, coatings for electrolytes, electrodes, membranes, and catalysts, and the like, are disclosed.

  19. A clustering based method to evaluate soil corrosivity for pipeline external integrity management

    International Nuclear Information System (INIS)

    Yajima, Ayako; Wang, Hui; Liang, Robert Y.; Castaneda, Homero

    2015-01-01

    One important category of transportation infrastructure is underground pipelines. Corrosion of these buried pipeline systems may cause pipeline failures with the attendant hazards of property loss and fatalities. Therefore, developing the capability to estimate the soil corrosivity is important for designing and preserving materials and for risk assessment. The deterioration rate of metal is highly influenced by the physicochemical characteristics of a material and the environment of its surroundings. In this study, the field data obtained from the southeast region of Mexico was examined using various data mining techniques to determine the usefulness of these techniques for clustering soil corrosivity level. Specifically, the soil was classified into different corrosivity level clusters by k-means and Gaussian mixture model (GMM). In terms of physical space, GMM shows better separability; therefore, the distributions of the material loss of the buried petroleum pipeline walls were estimated via the empirical density within GMM clusters. The soil corrosivity levels of the clusters were determined based on the medians of metal loss. The proposed clustering method was demonstrated to be capable of classifying the soil into different levels of corrosivity severity. - Highlights: • The clustering approach is applied to the data extracted from a real-life pipeline system. • Soil properties in the right-of-way are analyzed via clustering techniques to assess corrosivity. • GMM is selected as the preferred method for detecting the hidden pattern of in-situ data. • K–W test is performed for significant difference of corrosivity level between clusters

  20. Relation between financial market structure and the real economy: comparison between clustering methods.

    Science.gov (United States)

    Musmeci, Nicoló; Aste, Tomaso; Di Matteo, T

    2015-01-01

    We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  1. Relation between financial market structure and the real economy: comparison between clustering methods.

    Directory of Open Access Journals (Sweden)

    Nicoló Musmeci

    Full Text Available We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification. We apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree and we compare it with other methods including the Linkage and k-medoids. By taking the industrial sector classification of stocks as a benchmark partition, we evaluate how the different methods retrieve this classification. The results show that the Directed Bubble Hierarchical Tree can outperform other methods, being able to retrieve more information with fewer clusters. Moreover,we show that the economic information is hidden at different levels of the hierarchical structures depending on the clustering method. The dynamical analysis on a rolling window also reveals that the different methods show different degrees of sensitivity to events affecting financial markets, like crises. These results can be of interest for all the applications of clustering methods to portfolio optimization and risk hedging [corrected].

  2. SPATIALLY RESOLVED SPECTROSCOPY AND CHEMICAL HISTORY OF STAR-FORMING GALAXIES IN THE HERCULES CLUSTER: THE EFFECTS OF THE ENVIRONMENT

    International Nuclear Information System (INIS)

    Petropoulou, V.; Vilchez, J.; Iglesias-Paramo, J.; Cedres, B.; Papaderos, P.; Magrini, L.; Reverte, D.

    2011-01-01

    Spatially resolved spectroscopy has been obtained for a sample of 27 star-forming (SF) galaxies selected from our deep Hα survey of the Hercules cluster. We have applied spectral synthesis models to all emission-line spectra of this sample using the population synthesis code STARLIGHT and have obtained fundamental parameters of stellar components such as mean metallicity and age. The emission-line spectra were corrected for underlying stellar absorption using these spectral synthesis models. Line fluxes were measured and O/H and N/O gas chemical abundances were obtained using the latest empirical calibrations. We have derived the masses and total luminosities of the galaxies using available Sloan Digital Sky Survey broadband photometry. The effects of cluster environment on the chemical evolution of galaxies and on their mass-metallicity (MZ) and luminosity-metallicity (LZ) relations were studied by combining the derived gas metallicities, the mean stellar metallicities and ages, the masses and luminosities of the galaxies, and their existing H I data. Our Hercules SF galaxies are divided into three main subgroups: (1) chemically evolved spirals with truncated ionized-gas disks and nearly flat oxygen gradients, demonstrating the effect of ram-pressure stripping; (2) chemically evolved dwarfs/irregulars populating the highest local densities, possible products of tidal interactions in preprocessing events; and (3) less metallic dwarf galaxies that appear to be 'newcomers' to the cluster and are experiencing pressure-triggered star formation. Most Hercules SF galaxies follow well-defined MZ and LZ sequences (for both O/H and N/O), though the dwarf/irregular galaxies located at the densest regions appear to be outliers to these global relations, suggesting a physical reason for the dispersion in these fundamental relations. The Hercules cluster appears to be currently assembling via the merger of smaller substructures, providing an ideal laboratory where the local

  3. Trend analysis using non-stationary time series clustering based on the finite element method

    Science.gov (United States)

    Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.

    2014-05-01

    In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.

  4. Phenotypic clustering: a novel method for microglial morphology analysis.

    Science.gov (United States)

    Verdonk, Franck; Roux, Pascal; Flamant, Patricia; Fiette, Laurence; Bozza, Fernando A; Simard, Sébastien; Lemaire, Marc; Plaud, Benoit; Shorte, Spencer L; Sharshar, Tarek; Chrétien, Fabrice; Danckaert, Anne

    2016-06-17

    Microglial cells are tissue-resident macrophages of the central nervous system. They are extremely dynamic, sensitive to their microenvironment and present a characteristic complex and heterogeneous morphology and distribution within the brain tissue. Many experimental clues highlight a strong link between their morphology and their function in response to aggression. However, due to their complex "dendritic-like" aspect that constitutes the major pool of murine microglial cells and their dense network, precise and powerful morphological studies are not easy to realize and complicate correlation with molecular or clinical parameters. Using the knock-in mouse model CX3CR1(GFP/+), we developed a 3D automated confocal tissue imaging system coupled with morphological modelling of many thousands of microglial cells revealing precise and quantitative assessment of major cell features: cell density, cell body area, cytoplasm area and number of primary, secondary and tertiary processes. We determined two morphological criteria that are the complexity index (CI) and the covered environment area (CEA) allowing an innovative approach lying in (i) an accurate and objective study of morphological changes in healthy or pathological condition, (ii) an in situ mapping of the microglial distribution in different neuroanatomical regions and (iii) a study of the clustering of numerous cells, allowing us to discriminate different sub-populations. Our results on more than 20,000 cells by condition confirm at baseline a regional heterogeneity of the microglial distribution and phenotype that persists after induction of neuroinflammation by systemic injection of lipopolysaccharide (LPS). Using clustering analysis, we highlight that, at resting state, microglial cells are distributed in four microglial sub-populations defined by their CI and CEA with a regional pattern and a specific behaviour after challenge. Our results counteract the classical view of a homogenous regional resting

  5. Chemical Methods to Knock Down the Amyloid Proteins

    Directory of Open Access Journals (Sweden)

    Na Gao

    2017-06-01

    Full Text Available Amyloid proteins are closely related with amyloid diseases and do tremendous harm to human health. However, there is still a lack of effective strategies to treat these amyloid diseases, so it is important to develop novel methods. Accelerating the clearance of amyloid proteins is a favorable method for amyloid disease treatment. Recently, chemical methods for protein reduction have been developed and have attracted much attention. In this review, we focus on the latest progress of chemical methods that knock down amyloid proteins, including the proteolysis-targeting chimera (PROTAC strategy, the “recognition-cleavage” strategy, the chaperone-mediated autophagy (CMA strategy, the selectively light-activatable organic and inorganic molecules strategy and other chemical strategies.

  6. Correction for dispersion and Coulombic interactions in molecular clusters with density functional derived methods: Application to polycyclic aromatic hydrocarbon clusters

    Science.gov (United States)

    Rapacioli, Mathias; Spiegelman, Fernand; Talbi, Dahbia; Mineva, Tzonka; Goursot, Annick; Heine, Thomas; Seifert, Gotthard

    2009-06-01

    The density functional based tight binding (DFTB) is a semiempirical method derived from the density functional theory (DFT). It inherits therefore its problems in treating van der Waals clusters. A major error comes from dispersion forces, which are poorly described by commonly used DFT functionals, but which can be accounted for by an a posteriori treatment DFT-D. This correction is used for DFTB. The self-consistent charge (SCC) DFTB is built on Mulliken charges which are known to give a poor representation of Coulombic intermolecular potential. We propose to calculate this potential using the class IV/charge model 3 definition of atomic charges. The self-consistent calculation of these charges is introduced in the SCC procedure and corresponding nuclear forces are derived. Benzene dimer is then studied as a benchmark system with this corrected DFTB (c-DFTB-D) method, but also, for comparison, with the DFT-D. Both methods give similar results and are in agreement with references calculations (CCSD(T) and symmetry adapted perturbation theory) calculations. As a first application, pyrene dimer is studied with the c-DFTB-D and DFT-D methods. For coronene clusters, only the c-DFTB-D approach is used, which finds the sandwich configurations to be more stable than the T-shaped ones.

  7. Novel Clustering Method Based on K-Medoids and Mobility Metric

    Directory of Open Access Journals (Sweden)

    Y. Hamzaoui

    2018-06-01

    Full Text Available The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head.

  8. A simple and fast method to determine the parameters for fuzzy c-means cluster analysis

    DEFF Research Database (Denmark)

    Schwämmle, Veit; Jensen, Ole Nørregaard

    2010-01-01

    MOTIVATION: Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional datasets, such as those obtained in DNA microarray and quantitative proteomics experiments. One of its main limitations is the lack of a computationally fast method to set optimal values...... of algorithm parameters. Wrong parameter values may either lead to the inclusion of purely random fluctuations in the results or ignore potentially important data. The optimal solution has parameter values for which the clustering does not yield any results for a purely random dataset but which detects cluster...... formation with maximum resolution on the edge of randomness. RESULTS: Estimation of the optimal parameter values is achieved by evaluation of the results of the clustering procedure applied to randomized datasets. In this case, the optimal value of the fuzzifier follows common rules that depend only...

  9. Effect of drying methods on the chemical composition of three ...

    African Journals Online (AJOL)

    Three methods of drying (oven, sun and smoke) were used to dry Bonga spp., Sardinella spp. and Heterotis niloticus. The physico-chemical and minerals contents of the sample were determined using standard methods. Oven dried H. niloticus recorded the highest (16.42%) moisture content while the least moisture content ...

  10. A identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongping

    2006-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of Detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on the theory discussed above. (authors)

  11. Identification system for chemical warfare agents with PGNAA method

    International Nuclear Information System (INIS)

    Wang Bairong; Yin Guanghua; Yang Zhongpin

    2007-01-01

    The principle and the experimental commanding of Chemical warfare Agents Identification with PGNAA method are discussed in this paper. The choosing of detector, neutron source and the data processing method are detailed. Finally, a set of experimental instruments composed of Cf-232 and BGO detector is developed based on this theory discussed above. (authors)

  12. Methods of uranium isotpic separation by chemical exchange chromatography

    International Nuclear Information System (INIS)

    Pena V, L.A.; Valle M, L.

    1985-01-01

    Chemical exchange chromatography as applied to isotope separation has undergone a constant development during the last few years. The results so far indicate that this method could eventually become commercially useful. This work presents a critical review of the experimental methods presently under study by principal research groups, and which have not get been compared. (Author)

  13. Insights: A New Method to Balance Chemical Equations.

    Science.gov (United States)

    Garcia, Arcesio

    1987-01-01

    Describes a method designed to balance oxidation-reduction chemical equations. Outlines a method which is based on changes in the oxidation number that can be applied to both molecular reactions and ionic reactions. Provides examples and delineates the steps to follow for each type of equation balancing. (TW)

  14. New methods of sup(111)In chemical separation

    International Nuclear Information System (INIS)

    Santos, D.F.; Osso Junior, J.A.; Bastos, M.A.V.; Britto, J.L.Q.; Silva, R.F.

    1986-01-01

    The cation exchange and thermochromatography methods for chemical separation of sup(111) In from silver targets are described. The cation exchange method is based on the difference between In and Ag distribution coefficients on cation exchange resin treated with HNO sub(3). The thermochromatography consists of indium diffusion on silver melted after sublimation and posterior condensation. (M.C.K.)

  15. A semi-supervised method to detect seismic random noise with fuzzy GK clustering

    International Nuclear Information System (INIS)

    Hashemi, Hosein; Javaherian, Abdolrahim; Babuska, Robert

    2008-01-01

    We present a new method to detect random noise in seismic data using fuzzy Gustafson–Kessel (GK) clustering. First, using an adaptive distance norm, a matrix is constructed from the observed seismic amplitudes. The next step is to find centres of ellipsoidal clusters and construct a partition matrix which determines the soft decision boundaries between seismic events and random noise. The GK algorithm updates the cluster centres in order to iteratively minimize the cluster variance. Multiplication of the fuzzy membership function with values of each sample yields new sections; we name them 'clustered sections'. The seismic amplitude values of the clustered sections are given in a way to decrease the level of noise in the original noisy seismic input. In pre-stack data, it is essential to study the clustered sections in a f–k domain; finding the quantitative index for weighting the post-stack data needs a similar approach. Using the knowledge of a human specialist together with the fuzzy unsupervised clustering, the method is a semi-supervised random noise detection. The efficiency of this method is investigated on synthetic and real seismic data for both pre- and post-stack data. The results show a significant improvement of the input noisy sections without harming the important amplitude and phase information of the original data. The procedure for finding the final weights of each clustered section should be carefully done in order to keep almost all the evident seismic amplitudes in the output section. The method interactively uses the knowledge of the seismic specialist in detecting the noise

  16. Supersonic cluster beams: a powerful method for the deposition of nanostructured thin films with tailored properties

    International Nuclear Information System (INIS)

    Milani, P.

    2002-01-01

    By using a pulsed micro-plasma cluster source and by exploiting aero-dynamical effects typical of supersonic beams it is possible to obtain very high deposition rates with a control on neutral cluster mass distribution, allowing the deposition of thin films with controlled nanostructure. Due to high deposition rates, high lateral resolution, low temperature processing supersonic cluster beams can also be used for the micro and nano-patterning of cluster-assembled films when little or no post-growth manipulation or assembly is required. For example the nano and meso-structure of films obtained by carbon cluster beam deposition can be controlled by selecting in the beam the elemental building blocks, moreover functional properties such as field emission can be controlled and tailored. The use of supersonic cluster beams opens also new perspectives for the production of nano-structured films with novel physico-chemical and topological properties such as nano-structured carbon matrices containing carbide and transition metal particles. (Author)

  17. Kinetic methods for measuring the temperature of clusters and nanoparticles in molecular beams

    International Nuclear Information System (INIS)

    Makarov, Grigorii N

    2011-01-01

    The temperature (internal energy) of clusters and nanoparticles is an important physical parameter which affects many of their properties and the character of processes they are involved in. At the same time, determining the temperature of free clusters and nanoparticles in molecular beams is a rather complicated problem because the temperature of small particles depends on their size. In this paper, recently developed kinetic methods for measuring the temperature of clusters and nanoparticles in molecular beams are reviewed. The definition of temperature in the present context is given, and how the temperature affects the properties of and the processes involving the particles is discussed. The temperature behavior of clusters and nanoparticles near a phase transition point is analyzed. Early methods for measuring the temperature of large clusters are briefly described. It is shown that, compared to other methods, new kinetic methods are more universal and applicable for determining the temperature of clusters and nanoparticles of practically any size and composition. The future development and applications of these methods are outlined. (reviews of topical problems)

  18. Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

    Science.gov (United States)

    Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

    2011-01-01

    Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

  19. Are clusters important in understanding the mechanisms in atmospheric pressure ionization? Part 1: Reagent ion generation and chemical control of ion populations.

    Science.gov (United States)

    Klee, Sonja; Derpmann, Valerie; Wißdorf, Walter; Klopotowski, Sebastian; Kersten, Hendrik; Brockmann, Klaus J; Benter, Thorsten; Albrecht, Sascha; Bruins, Andries P; Dousty, Faezeh; Kauppila, Tiina J; Kostiainen, Risto; O'Brien, Rob; Robb, Damon B; Syage, Jack A

    2014-08-01

    It is well documented since the early days of the development of atmospheric pressure ionization methods, which operate in the gas phase, that cluster ions are ubiquitous. This holds true for atmospheric pressure chemical ionization, as well as for more recent techniques, such as atmospheric pressure photoionization, direct analysis in real time, and many more. In fact, it is well established that cluster ions are the primary carriers of the net charge generated. Nevertheless, cluster ion chemistry has only been sporadically included in the numerous proposed ionization mechanisms leading to charged target analytes, which are often protonated molecules. This paper series, consisting of two parts, attempts to highlight the role of cluster ion chemistry with regard to the generation of analyte ions. In addition, the impact of the changing reaction matrix and the non-thermal collisions of ions en route from the atmospheric pressure ion source to the high vacuum analyzer region are discussed. This work addresses such issues as extent of protonation versus deuteration, the extent of analyte fragmentation, as well as highly variable ionization efficiencies, among others. In Part 1, the nature of the reagent ion generation is examined, as well as the extent of thermodynamic versus kinetic control of the resulting ion population entering the analyzer region.

  20. An improved K-means clustering method for cDNA microarray image segmentation.

    Science.gov (United States)

    Wang, T N; Li, T J; Shao, G F; Wu, S X

    2015-07-14

    Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

  1. Application Of WIMS Code To Calculation Kartini Reactor Parameters By Pin-Cell And Cluster Method

    International Nuclear Information System (INIS)

    Sumarsono, Bambang; Tjiptono, T.W.

    1996-01-01

    Analysis UZrH fuel element parameters calculation in Kartini Reactor by WIMS Code has been done. The analysis is done by pin cell and cluster method. The pin cell method is done as a function percent burn-up and by 8 group 3 region analysis and cluster method by 8 group 12 region analysis. From analysis and calculation resulted K ∼ = 1.3687 by pin cell method and K ∼ = 1.3162 by cluster method and so deviation is 3.83%. By pin cell analysis as a function percent burn-up at the percent burn-up greater than 59.50%, the multiplication factor is less than one (k ∼ < 1) it is mean that the fuel element reactivity is negative

  2. Ages and chemical compositions of massive globular clusters in NGC147 and M31

    Science.gov (United States)

    Sharina, Margarita; Shimansky, Vladislav

    2015-08-01

    We present estimates of ages, [Fe/H], helium contents (Y) and abundances of C, N, Mg, Ca, Ti, Cr, Mn, Co and Ni for the following globular clusters (GCs): 7 in NGC147, and Mayall II, Mackey 1 and Mackey 6 in M31. Medium-resolution integrated-light spectra of the GCs were conducted with the 6m telescope. To derive the ages and abundances for the GCs we carried out their population synthesis using model stellar atmospheres, the Padova YZVAR isochrones and the Chabrier mass function. We compare the results with the corresponding data obtained using the same method for several massive Galactic GCs. We show that the differences in the Mg and C abundances between GCs with similar ages and metallicities may reach 0.5-0.6 dex. The corresponding differences for other elements are usually ˜2-3 times smaller. We suggest that at least partially the detected differences may be due to Mg and C abundance variations in the atmospheres of high-luminosity red giant branch stars as a consequence of the transportation of the produced elements to the surface layers.

  3. Ages and chemical compositions of massive clusters in NGC147 and M31

    Science.gov (United States)

    Sharina, Margarita; Shimansky, Vladislav

    2017-03-01

    We present estimates of ages, [Fe/H], helium content (Y) and abundances of C, N, Mg, Ca, and several other elements for the following globular clusters (GCs): GC7 in NGC147, and Mayall II, Mackey 1 and Mackey 6 in M31. Medium-resolution integrated-light spectra of the GCs were conducted with the 6m telescope. To derive the ages and abundances for the GCs we carried out their population synthesis using model stellar atmospheres, the Padova YZVAR isochrones and the Chabrier mass function. We compare the results with the corresponding data obtained using the same method for several massive Galactic GCs. We show that the differences in the light-element abundances between GCs with similar ages and metallicities may reach 0.5-0.6 dex. The corresponding differences for other elements are usually 2-3 times smaller. We suggest that at least partially the detected differences may be due to light-element abundance variations in the atmospheres of high-luminosity red giant branch stars as a consequence of the transportation of the produced elements to the surface layers.

  4. The use of different clustering methods in the evaluation of genetic diversity in upland cotton

    Directory of Open Access Journals (Sweden)

    Laíse Ferreira de Araújo

    Full Text Available The continuous development and evaluation of new genotypes through crop breeding is essential in order to obtain new cultivars. The objective of this work was to evaluate the genetic divergences between cultivars of upland cotton (Gossypium hirsutum L. using the agronomic and technological characteristics of the fibre, in order to select superior parent plants. The experiment was set up during 2010 at the Federal University of Ceará in Fortaleza, Ceará, Brazil. Eleven cultivars of upland cotton were used in an experimental design of randomised blocks with three replications. In order to evaluate the genetic diversity among cultivars, the generalised Mahalanobis distance matrix was calculated, with cluster analysis then being applied, employing various methods: single linkage, Ward, complete linkage, median, average linkage within a cluster and average linkage between clusters. Genetic variability exists among the evaluated genotypes. The most consistant clustering method was that employing average linkage between clusters. Among the characteristics assessed, mean boll weight presented the highest contribution to genetic diversity, followed by elongation at rupture. Employing the method of mean linkage between clusters, the cultivars with greater genetic divergence were BRS Acacia and LD Frego; those of greater similarity were BRS Itaúba and BRS Araripe.

  5. A semantics-based method for clustering of Chinese web search results

    Science.gov (United States)

    Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

    2014-01-01

    Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

  6. A Spatial Shape Constrained Clustering Method for Mammographic Mass Segmentation

    Directory of Open Access Journals (Sweden)

    Jian-Yong Lou

    2015-01-01

    error of 7.18% for well-defined masses (or 8.06% for ill-defined masses was obtained by using DACF on MiniMIAS database, with 5.86% (or 5.55% and 6.14% (or 5.27% improvements as compared to the standard DA and fuzzy c-means methods.

  7. Adaptive cluster sampling: An efficient method for assessing inconspicuous species

    Science.gov (United States)

    Andrea M. Silletti; Joan Walker

    2003-01-01

    Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

  8. Chemical Fingerprint and Quantitative Analysis for the Quality Evaluation of Platycladi cacumen by Ultra-performance Liquid Chromatography Coupled with Hierarchical Cluster Analysis.

    Science.gov (United States)

    Shan, Mingqiu; Li, Sam Fong Yau; Yu, Sheng; Qian, Yan; Guo, Shuchen; Zhang, Li; Ding, Anwei

    2018-01-01

    Platycladi cacumen (dried twigs and leaves of Platycladus orientalis (L.) Franco) is a frequently utilized Chinese medicinal herb. To evaluate the quality of the phytomedcine, an ultra-performance liquid chromatographic method with diode array detection was established for chemical fingerprinting and quantitative analysis. In this study, 27 batches of P. cacumen from different regions were collected for analysis. A chemical fingerprint with 20 common peaks was obtained using Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A). Among these 20 components, seven flavonoids (myricitrin, isoquercitrin, quercitrin, afzelin, cupressuflavone, amentoflavone and hinokiflavone) were identified and determined simultaneously. In the method validation, the seven analytes showed good regressions (R ≥ 0.9995) within linear ranges and good recoveries from 96.4% to 103.3%. Furthermore, with the contents of these seven flavonoids, hierarchical clustering analysis was applied to distinguish the 27 batches into five groups. The chemometric results showed that these groups were almost consistent with geographical positions and climatic conditions of the production regions. Integrating fingerprint analysis, simultaneous determination and hierarchical clustering analysis, the established method is rapid, sensitive, accurate and readily applicable, and also provides a significant foundation for quality control of P. cacumen efficiently. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. Robustness of serial clustering of extratropical cyclones to the choice of tracking method

    Directory of Open Access Journals (Sweden)

    Joaquim G. Pinto

    2016-07-01

    Full Text Available Cyclone clusters are a frequent synoptic feature in the Euro-Atlantic area. Recent studies have shown that serial clustering of cyclones generally occurs on both flanks and downstream regions of the North Atlantic storm track, while cyclones tend to occur more regulary on the western side of the North Atlantic basin near Newfoundland. This study explores the sensitivity of serial clustering to the choice of cyclone tracking method using cyclone track data from 15 methods derived from ERA-Interim data (1979–2010. Clustering is estimated by the dispersion (ratio of variance to mean of winter [December – February (DJF] cyclone passages near each grid point over the Euro-Atlantic area. The mean number of cyclone counts and their variance are compared between methods, revealing considerable differences, particularly for the latter. Results show that all different tracking methods qualitatively capture similar large-scale spatial patterns of underdispersion and overdispersion over the study region. The quantitative differences can primarily be attributed to the differences in the variance of cyclone counts between the methods. Nevertheless, overdispersion is statistically significant for almost all methods over parts of the eastern North Atlantic and Western Europe, and is therefore considered as a robust feature. The influence of the North Atlantic Oscillation (NAO on cyclone clustering displays a similar pattern for all tracking methods, with one maximum near Iceland and another between the Azores and Iberia. The differences in variance between methods are not related with different sensitivities to the NAO, which can account to over 50% of the clustering in some regions. We conclude that the general features of underdispersion and overdispersion of extratropical cyclones over the North Atlantic and Western Europe are robust to the choice of tracking method. The same is true for the influence of the NAO on cyclone dispersion.

  10. Clustered vacancies in ZnO: chemical aspects and consequences on physical properties

    Science.gov (United States)

    Pal, S.; Gogurla, N.; Das, Avishek; Singha, S. S.; Kumar, Pravin; Kanjilal, D.; Singha, A.; Chattopadhyay, S.; Jana, D.; Sarkar, A.

    2018-03-01

    The chemical nature of point defects, their segregation, cluster or complex formation in ZnO is an important area of investigation. The evolution of a defective state with MeV Ar ion irradiation fluence 1  ×  1014 and 1  ×  1016 ions cm-2 has been monitored here using x-ray photoelectron spectroscopy (XPS), photoluminescence (PL) and Raman spectroscopy. The XPS study shows the presence of oxygen vacancies (V O) in Ar irradiated ZnO. Zn(LMM) Auger spectra clearly identifies a transition involving metallic zinc in the irradiated samples. An intense PL emission from interstitial Zn (I Zn)-related shallow donor bound excitons (DBX) is visible in the 10 K spectra for all samples. Although overall PL is largely reduced with irradiation disorder, DBX intensity is increased for the highest fluence irradiated sample. The Raman study indicates damage in both the zinc and oxygen sub-lattice by an energetic ion beam. Representative Raman modes from defect complexes involving V O, I Zn and I O are visible after irradiation with intermediate fluence. A further increase of fluence shows, to some extent, a homogenization of disorder. A huge reduction of resistance is also noted for this sample. Certainly, high irradiation fluence induces a qualitative modification of the conventional (and highly resistive) grain boundary (GB) structure of granular ZnO. A low resistive path, involving I Zn related shallow donors, across the GB can be presumed to explain resistance reduction. Open volumes (V Zn and V O) agglomerate more and more with increasing irradiation fluence and are finally transformed to voids. The results as a whole have been elucidated with a model which emphasizes the possible evolution of a new defect microstructure that is distinctively different from the GB-related disorder. Based on the model, qualitative explanations of commonly observed radiation hardness, colouration and ferromagnetism in disordered ZnO have been put forward. A coherent scenario

  11. APPLICATION OF CHEMICAL METHODS TO THE SOLID WASTE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    C. P. Bulimaga

    2008-12-01

    Full Text Available The present article is a synthesis analysis of application of chemical methods for the development of technologies of hazardous waste management. Here are offered some technologies of neutralization of the waste containing hexacyanofferates, galvanic wastes and those with contain of vanadium, which are collected at Power Thermoelectric Plants.

  12. Comparison of traditional physico-chemical methods and molecular ...

    African Journals Online (AJOL)

    This study was aim to review the efficiency of molecular markers and traditional physico-chemical methods for the identification of basmati rice. The study involved 44 promising varieties of Indica rices collected from geographically distant places and adapted to irrigated and aerobic agro-ecosystems. Quality data for ...

  13. Effect of integration of cultural, botanical, and chemical methods of ...

    African Journals Online (AJOL)

    A field experiment was conducted from November 2011 to June 2013 to evaluate the effects of botanical, cultural, and chemical methods on termite colony survival, crop and wooden damage, and other biological activities in Ghimbi district of western Ethiopia. The termite mounds were dug and the following treatments were ...

  14. An effective trust-based recommendation method using a novel graph clustering algorithm

    Science.gov (United States)

    Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

    2015-10-01

    Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

  15. MHCcluster, a method for functional clustering of MHC molecules

    DEFF Research Database (Denmark)

    Thomsen, Martin Christen Frølund; Lundegaard, Claus; Buus, Søren

    2013-01-01

    The identification of peptides binding to major histocompatibility complexes (MHC) is a critical step in the understanding of T cell immune responses. The human MHC genomic region (HLA) is extremely polymorphic comprising several thousand alleles, many encoding a distinct molecule. The potentially...... binding specificity. The method has a flexible web interface that allows the user to include any MHC of interest in the analysis. The output consists of a static heat map and graphical tree-based visualizations of the functional relationship between MHC variants and a dynamic TreeViewer interface where...

  16. Electrochemical and chemical methods of metallizing plastic films

    OpenAIRE

    Chapples, J.

    1991-01-01

    This thesis describes two novel techniques for the metallization of non-electroactive polymer films and thicker sectioned polyethylene and nylon substrates. In the first approach, non-electroactive polymer substrates were impregnated with surface layers of polypyrrole and polyaniline, using electrochemical and chemical methods of polymerization. The relative merits of both these approaches are discussed and compared with other methods in the literature. The resultant composi...

  17. Pseudo-potential method for taking into account the Pauli principle in cluster systems

    International Nuclear Information System (INIS)

    Krasnopol'skii, V.M.; Kukulin, V.I.

    1975-01-01

    In order to take account of the Pauli principle in cluster systems (such as 3α, α + α + n) a convenient method of renormalization of the cluster-cluster deep attractive potentials with forbidden states is suggested. The renormalization consists of adding projectors upon the occupied states with an infinite coupling constant to the initial deep potential which means that we pass to pseudo-potentials. The pseudo-potential approach in projecting upon the noneigenstates is shown to be equivalent to the orthogonality condition model of Saito et al. The orthogonality of the many-particle wave function to the forbidden states of each two-cluster sub-system is clearly demonstrated

  18. Test computations on the dynamical evolution of star clusters. [Fluid dynamic method

    Energy Technology Data Exchange (ETDEWEB)

    Angeletti, L; Giannone, P. (Rome Univ. (Italy))

    1977-01-01

    Test calculations have been carried out on the evolution of star clusters using the fluid-dynamical method devised by Larson (1970). Large systems of stars have been considered with specific concern with globular clusters. With reference to the analogous 'standard' model by Larson, the influence of varying in turn the various free parameters (cluster mass, star mass, tidal radius, mass concentration of the initial model) has been studied for the results. Furthermore, the partial release of some simplifying assumptions with regard to the relaxation time and distribution of the 'target' stars has been considered. The change of the structural properties is discussed, and the variation of the evolutionary time scale is outlined. An indicative agreement of the results obtained here with structural properties of globular clusters as deduced from previous theoretical models is pointed out.

  19. The resonating group method three cluster approach to the ground state 9 Li nucleus structure

    International Nuclear Information System (INIS)

    Filippov, G.F.; Pozdnyakov, Yu.A.; Terenetsky, K.O.; Verbitsky, V.P.

    1994-01-01

    The three-cluster approach for light atomic nuclei is formulated in frame of the algebraic version of resonating group method. Overlap integral and Hamiltonian matrix elements on generating functions are obtained for 9 Li nucleus. All permissible by Pauli principle 9 Li different cluster nucleon permutations were taken into account in the calculations. The results obtained can be easily generalised on any three-cluster system up to 12 C. Matrix elements obtained in the work were used in the variational calculations of the ground state energetic and geometric 9 Li characteristics. It is shown that 9 Li ground state is not adequate to the shell model limit and has pronounced three-cluster structure. (author). 16 refs., 4 tab., 2 figs

  20. A New Soft Computing Method for K-Harmonic Means Clustering.

    Science.gov (United States)

    Yeh, Wei-Chang; Jiang, Yunzhi; Chen, Yee-Fen; Chen, Zhe

    2016-01-01

    The K-harmonic means clustering algorithm (KHM) is a new clustering method used to group data such that the sum of the harmonic averages of the distances between each entity and all cluster centroids is minimized. Because it is less sensitive to initialization than K-means (KM), many researchers have recently been attracted to studying KHM. In this study, the proposed iSSO-KHM is based on an improved simplified swarm optimization (iSSO) and integrates a variable neighborhood search (VNS) for KHM clustering. As evidence of the utility of the proposed iSSO-KHM, we present extensive computational results on eight benchmark problems. From the computational results, the comparison appears to support the superiority of the proposed iSSO-KHM over previously developed algorithms for all experiments in the literature.

  1. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.

  2. Soil chemical sensor and precision agricultural chemical delivery system and method

    Science.gov (United States)

    Colburn, Jr., John W.

    1991-01-01

    A real time soil chemical sensor and precision agricultural chemical delivery system includes a plurality of ground-engaging tools in association with individual soil sensors which measure soil chemical levels. The system includes the addition of a solvent which rapidly saturates the soil/tool interface to form a conductive solution of chemicals leached from the soil. A multivalent electrode, positioned within a multivalent frame of the ground-engaging tool, applies a voltage or impresses a current between the electrode and the tool frame. A real-time soil chemical sensor and controller senses the electrochemical reaction resulting from the application of the voltage or current to the leachate, measures it by resistivity methods, and compares it against pre-set resistivity levels for substances leached by the solvent. Still greater precision is obtained by calibrating for the secondary current impressed through solvent-less soil. The appropriate concentration is then found and the servo-controlled delivery system applies the appropriate amount of fertilizer or agricultural chemicals substantially in the location from which the soil measurement was taken.

  3. Quantum chemical study of the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters

    Science.gov (United States)

    Linton, Kirsty A.; Wright, Timothy G.; Besley, Nicholas A.

    2018-03-01

    Quantum chemical methods including Møller-Plesset perturbation (MP2) theory and density functional theory (DFT) have been used to study the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters. MP2/6-311++G** calculations are shown to describe the structure and spectroscopy of the clusters well. DFT calculations with exchange-correlation functionals with a low fraction of Hartree-Fock exchange give a binding energy of NO+.(H2O) that is too high and incorrectly predict the lowest energy structure of NO+.(H2O)2, and this error may be associated with a delocalization of charge onto the water molecule directly binding to NO+. Ab initio molecular dynamics (AIMD) simulations were performed to study the NO+.(H2O)5 H+.(H2O)4 + HONO reaction to investigate the formation of HONO from NO+.(H2O)5. Whether an intracluster reaction to form HONO is observed depends on the level of electronic structure theory used. Of note is that methods that accurately describe the relative energies of the product and reactant clusters did not show reactions on the timescales studied. This suggests that in the upper atmosphere the reaction may occur owing to the energy present in the NO+.(H2O)5 complex following its formation. This article is part of the theme issue `Modern theoretical chemistry'.

  4. Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification

    Directory of Open Access Journals (Sweden)

    Yajie Zou

    2017-01-01

    Full Text Available Hotspot identification (HSID is a critical part of network-wide safety evaluations. Typical methods for ranking sites are often rooted in using the Empirical Bayes (EB method to estimate safety from both observed crash records and predicted crash frequency based on similar sites. The performance of the EB method is highly related to the selection of a reference group of sites (i.e., roadway segments or intersections similar to the target site from which safety performance functions (SPF used to predict crash frequency will be developed. As crash data often contain underlying heterogeneity that, in essence, can make them appear to be generated from distinct subpopulations, methods are needed to select similar sites in a principled manner. To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering to select “similar” sites for building SPFs are developed. Performance of the clustering-based EB methods is then compared using real crash data. Here, HSID results, when computed on Texas undivided rural highway cash data, suggest that all three clustering-based EB analysis methods are preferred over the conventional statistical methods. Thus, properly classifying the road segments for heterogeneous crash data can further improve HSID accuracy.

  5. Cluster Analysis of the Newcastle Electronic Corpus of Tyneside English: A Comparison of Methods

    NARCIS (Netherlands)

    Moisl, Hermann; Jones, Valerie M.

    2005-01-01

    This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different

  6. Cluster Analysis of the Newcastle Electronic Corpus of Tyneside English: In A Comparison of Methods

    NARCIS (Netherlands)

    Moisl, Hermann; Jones, Valerie M.

    2005-01-01

    This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different

  7. System and Method for Outlier Detection via Estimating Clusters

    Science.gov (United States)

    Iverson, David J. (Inventor)

    2016-01-01

    An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

  8. A method of detecting spatial clustering of disease

    International Nuclear Information System (INIS)

    Openshaw, S.; Wilkie, D.; Binks, K.; Wakeford, R.; Gerrard, M.H.; Croasdale, M.R.

    1989-01-01

    A statistical technique has been developed to identify extreme groupings of a disease and is being applied to childhood cancers, initially to acute lymphoblastic leukaemia incidence in the Northern and North-Western Regions of England. The method covers the area with a square grid, the size of which is varied over a wide range and whose origin is moved in small increments in two directions. The population at risk within any square is estimated using the 1971 and 1981 censuses. The significance of an excess of disease is determined by random simulation. In addition, tests to detect a general departure from a background Poisson process are carried out. Available results will be presented at the conference. (author)

  9. A method for determining the radius of an open cluster from stellar proper motions

    Science.gov (United States)

    Sánchez, Néstor; Alfaro, Emilio J.; López-Martínez, Fátima

    2018-04-01

    We propose a method for calculating the radius of an open cluster in an objective way from an astrometric catalogue containing, at least, positions and proper motions. It uses the minimum spanning tree in the proper motion space to discriminate cluster stars from field stars and it quantifies the strength of the cluster-field separation by means of a statistical parameter defined for the first time in this paper. This is done for a range of different sampling radii from where the cluster radius is obtained as the size at which the best cluster-field separation is achieved. The novelty of this strategy is that the cluster radius is obtained independently of how its stars are spatially distributed. We test the reliability and robustness of the method with both simulated and real data from a well-studied open cluster (NGC 188), and apply it to UCAC4 data for five other open clusters with different catalogued radius values. NGC 188, NGC 1647, NGC 6603, and Ruprecht 155 yielded unambiguous radius values of 15.2 ± 1.8, 29.4 ± 3.4, 4.2 ± 1.7, and 7.0 ± 0.3 arcmin, respectively. ASCC 19 and Collinder 471 showed more than one possible solution, but it is not possible to know whether this is due to the involved uncertainties or due to the presence of complex patterns in their proper motion distributions, something that could be inherent to the physical object or due to the way in which the catalogue was sampled.

  10. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

  11. Analysis of cost data in a cluster-randomized, controlled trial: comparison of methods

    DEFF Research Database (Denmark)

    Sokolowski, Ineta; Ørnbøl, Eva; Rosendal, Marianne

    studies have used non-valid analysis of skewed data. We propose two different methods to compare mean cost in two groups. Firstly, we use a non-parametric bootstrap method where the re-sampling takes place on two levels in order to take into account the cluster effect. Secondly, we proceed with a log......-transformation of the cost data and apply the normal theory on these data. Again we try to account for the cluster effect. The performance of these two methods is investigated in a simulation study. The advantages and disadvantages of the different approaches are discussed.......  We consider health care data from a cluster-randomized intervention study in primary care to test whether the average health care costs among study patients differ between the two groups. The problems of analysing cost data are that most data are severely skewed. Median instead of mean...

  12. Charge-doping and chemical composition-driven magnetocrystalline anisotropy in CoPt core-shell alloy clusters

    Science.gov (United States)

    Ruiz-Díaz, P.; Muñoz-Navia, M.; Dorantes-Dávila, J.

    2018-03-01

    Charge-doping together with 3 d-4 d alloying emerges as promising mechanisms for tailoring the magnetic properties of low-dimensional systems. Here, throughout ab initio calculations, we present a systematic overview regarding the impact of both electron(hole) charge-doping and chemical composition on the magnetocrystalline anisotropy (MA) of CoPt core-shell alloy clusters. By taking medium-sized Co n Pt m ( N = n + m = 85) octahedral-like alloy nanoparticles for some illustrative core-sizes as examples, we found enhanced MA energies and large induced spin(orbital) moments in Pt-rich clusters. Moreover, depending on the Pt-core-size, both in-plane and off-plane directions of magnetization are observed. In general, the MA of these binary compounds further stabilizes upon charge-doping. In addition, in the clusters with small MA, the doping promotes magnetization switching. Insights into the microscopical origins of the MA behavior are associated to changes in the electronic structure of the clusters. [Figure not available: see fulltext.

  13. Identification of rural landscape classes through a GIS clustering method

    Directory of Open Access Journals (Sweden)

    Irene Diti

    2013-09-01

    Full Text Available The paper presents a methodology aimed at supporting the rural planning process. The analysis of the state of the art of local and regional policies focused on rural and suburban areas, and the study of the scientific literature in the field of spatial analysis methodologies, have allowed the definition of the basic concept of the research. The proposed method, developed in a GIS, is based on spatial metrics selected and defined to cover various agricultural, environmental, and socio-economic components. The specific goal of the proposed methodology is to identify homogeneous extra-urban areas through their objective characterization at different scales. Once areas with intermediate urban-rural characters have been identified, the analysis is then focused on the more detailed definition of periurban agricultural areas. The synthesis of the results of the analysis of the various landscape components is achieved through an original interpretative key which aims to quantify the potential impacts of rural areas on the urban system. This paper presents the general framework of the methodology and some of the main results of its first implementation through an Italian case study.

  14. Manual of selected physico-chemical analytical methods. IV

    International Nuclear Information System (INIS)

    Beran, M.; Klosova, E.; Krtil, J.; Sus, F.; Kuvik, V.; Vrbova, L.; Hamplova, M.; Lengyel, J.; Kelnar, L.; Zakouril, K.

    1990-11-01

    The Central Testing Laboratory of the Nuclear Research Institute at Rez has for a decade been participating in the development of analytical procedures and has been providing analyses of samples of different types and origin. The analytical procedures developed have been published in special journals and a number of them in the Manuals of analytical methods, in three parts. The 4th part of the Manual contains selected physico-chemical methods developed or modified by the Laboratory in the years 1986-1990 within the project ''Development of physico-chemical analytical methods''. In most cases, techniques are involved for non-nuclear applications. Some can find wider applications, especially in analyses of environmental samples. Others have been developed for specific cases of sample analyses or require special instrumentation (mass spectrometer), which partly restricts their applicability by other institutions. (author)

  15. Method for fractional solid-waste sampling and chemical analysis

    DEFF Research Database (Denmark)

    Riber, Christian; Rodushkin, I.; Spliid, Henrik

    2007-01-01

    four subsampling methods and five digestion methods, paying attention to the heterogeneity and the material characteristics of the waste fractions, it was possible to determine 61 substances with low detection limits, reasonable variance, and high accuracy. For most of the substances of environmental...... of variance (20-85% of the overall variation). Only by increasing the sample size significantly can this variance be reduced. The accuracy and short-term reproducibility of the chemical characterization were good, as determined by the analysis of several relevant certified reference materials. Typically, six...... to eight different certified reference materials representing a range of concentrations levels and matrix characteristics were included. Based on the documentation provided, the methods introduced were considered satisfactory for characterization of the chemical composition of waste-material fractions...

  16. Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

    Science.gov (United States)

    Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

    2016-01-01

    Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  17. Method for innovative synthesis-design of chemical process flowsheets

    DEFF Research Database (Denmark)

    Kumar Tula, Anjan; Gani, Rafiqul

    Chemical process synthesis-design involve the identification of the processing route to reach a desired product from a specified set of raw materials, design of the operations involved in the processing route, the calculations of utility requirements, the calculations of waste and emission...... to the surrounding and many more. Different methods (knowledge-based [1], mathematical programming [2], hybrid, etc.) have been proposed and are also currently employed to solve these synthesis-design problems. D’ Anterroches [3] proposed a group contribution based approach to solve the synthesis-design problem...... of chemical processes, where, chemical process flowsheets could be synthesized in the same way as atoms or groups of atoms are synthesized to form molecules in computer aided molecular design (CAMD) techniques [4]. That, from a library of building blocks (functional process-groups) and a set of rules to join...

  18. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    Directory of Open Access Journals (Sweden)

    Qiao Wei

    2017-01-01

    Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

  19. AN EFFICIENT INITIALIZATION METHOD FOR K-MEANS CLUSTERING OF HYPERSPECTRAL DATA

    Directory of Open Access Journals (Sweden)

    A. Alizade Naeini

    2014-10-01

    Full Text Available K-means is definitely the most frequently used partitional clustering algorithm in the remote sensing community. Unfortunately due to its gradient decent nature, this algorithm is highly sensitive to the initial placement of cluster centers. This problem deteriorates for the high-dimensional data such as hyperspectral remotely sensed imagery. To tackle this problem, in this paper, the spectral signatures of the endmembers in the image scene are extracted and used as the initial positions of the cluster centers. For this purpose, in the first step, A Neyman–Pearson detection theory based eigen-thresholding method (i.e., the HFC method has been employed to estimate the number of endmembers in the image. Afterwards, the spectral signatures of the endmembers are obtained using the Minimum Volume Enclosing Simplex (MVES algorithm. Eventually, these spectral signatures are used to initialize the k-means clustering algorithm. The proposed method is implemented on a hyperspectral dataset acquired by ROSIS sensor with 103 spectral bands over the Pavia University campus, Italy. For comparative evaluation, two other commonly used initialization methods (i.e., Bradley & Fayyad (BF and Random methods are implemented and compared. The confusion matrix, overall accuracy and Kappa coefficient are employed to assess the methods’ performance. The evaluations demonstrate that the proposed solution outperforms the other initialization methods and can be applied for unsupervised classification of hyperspectral imagery for landcover mapping.

  20. Multishell method: Exact treatment of a cluster in an effective medium

    International Nuclear Information System (INIS)

    Gonis, A.; Garland, J.W.

    1977-01-01

    A method is presented for the exact determination of the Green's function of a cluster embedded in a given effective medium. This method, the multishell method, is applicable even to systems with off-diagonal disorder, extended-range hopping, multiple bands, and/or hybridization, and is computationally practicable for any system described by a tight-binding or interpolation-scheme Hamiltonian. It allows one to examine the effects of local environment on the densities of states and site spectral weight functions of disordered systems. For any given analytic effective medium characterized by a non-negative density of states the method yields analytic cluster Green's functions and non-negative site spectral weight functions. Previous methods used for the calculation of the Green's function of a cluster embedded in a given effective medium have not been exact. The results of numerical calculations for model systems show that even the best of these previous methods can lead to substantial errors, at least for small clusters in two- and three-dimensional lattices. These results also show that fluctuations in local environment have large effects on site spectral weight functions, even in cases in which the single-site coherent-potential approximation yields an accurate overall density of states

  1. Open-Source Sequence Clustering Methods Improve the State Of the Art.

    Science.gov (United States)

    Kopylova, Evguenia; Navas-Molina, Jose A; Mercier, Céline; Xu, Zhenjiang Zech; Mahé, Frédéric; He, Yan; Zhou, Hong-Wei; Rognes, Torbjørn; Caporaso, J Gregory; Knight, Rob

    2016-01-01

    Sequence clustering is a common early step in amplicon-based microbial community analysis, when raw sequencing reads are clustered into operational taxonomic units (OTUs) to reduce the run time of subsequent analysis steps. Here, we evaluated the performance of recently released state-of-the-art open-source clustering software products, namely, OTUCLUST, Swarm, SUMACLUST, and SortMeRNA, against current principal options (UCLUST and USEARCH) in QIIME, hierarchical clustering methods in mothur, and USEARCH's most recent clustering algorithm, UPARSE. All the latest open-source tools showed promising results, reporting up to 60% fewer spurious OTUs than UCLUST, indicating that the underlying clustering algorithm can vastly reduce the number of these derived OTUs. Furthermore, we observed that stringent quality filtering, such as is done in UPARSE, can cause a significant underestimation of species abundance and diversity, leading to incorrect biological results. Swarm, SUMACLUST, and SortMeRNA have been included in the QIIME 1.9.0 release. IMPORTANCE Massive collections of next-generation sequencing data call for fast, accurate, and easily accessible bioinformatics algorithms to perform sequence clustering. A comprehensive benchmark is presented, including open-source tools and the popular USEARCH suite. Simulated, mock, and environmental communities were used to analyze sensitivity, selectivity, species diversity (alpha and beta), and taxonomic composition. The results demonstrate that recent clustering algorithms can significantly improve accuracy and preserve estimated diversity without the application of aggressive filtering. Moreover, these tools are all open source, apply multiple levels of multithreading, and scale to the demands of modern next-generation sequencing data, which is essential for the analysis of massive multidisciplinary studies such as the Earth Microbiome Project (EMP) (J. A. Gilbert, J. K. Jansson, and R. Knight, BMC Biol 12:69, 2014, http

  2. Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

    Science.gov (United States)

    Luo, Congpei; He, Tao; Chun, Ze

    2013-04-01

    Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.

  3. Form gene clustering method about pan-ethnic-group products based on emotional semantic

    Science.gov (United States)

    Chen, Dengkai; Ding, Jingjing; Gao, Minzhuo; Ma, Danping; Liu, Donghui

    2016-09-01

    The use of pan-ethnic-group products form knowledge primarily depends on a designer's subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers' perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

  4. Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

    Science.gov (United States)

    Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

    2018-02-01

    Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

  5. Unsupervised Learning —A Novel Clustering Method for Rolling Bearing Faults Identification

    Science.gov (United States)

    Kai, Li; Bo, Luo; Tao, Ma; Xuefeng, Yang; Guangming, Wang

    2017-12-01

    To promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rolling bearing. Among these studies, such as artificial neural networks, support vector machines, decision trees and other supervised learning methods are used commonly. These methods can detect the failure of rolling bearing effectively, but to achieve better detection results, it often requires a lot of training samples. Based on above, a novel clustering method is proposed in this paper. This novel method is able to find the correct number of clusters automatically the effectiveness of the proposed method is validated using datasets from rolling element bearings. The diagnosis results show that the proposed method can accurately detect the fault types of small samples. Meanwhile, the diagnosis results are also relative high accuracy even for massive samples.

  6. Clustering of attitudes towards obesity: a mixed methods study of Australian parents and children.

    Science.gov (United States)

    Olds, Tim; Thomas, Samantha; Lewis, Sophie; Petkov, John

    2013-10-12

    Current population-based anti-obesity campaigns often target individuals based on either weight or socio-demographic characteristics, and give a 'mass' message about personal responsibility. There is a recognition that attempts to influence attitudes and opinions may be more effective if they resonate with the beliefs that different groups have about the causes of, and solutions for, obesity. Limited research has explored how attitudinal factors may inform the development of both upstream and downstream social marketing initiatives. Computer-assisted face-to-face interviews were conducted with 159 parents and 184 of their children (aged 9-18 years old) in two Australian states. A mixed methods approach was used to assess attitudes towards obesity, and elucidate why different groups held various attitudes towards obesity. Participants were quantitatively assessed on eight dimensions relating to the severity and extent, causes and responsibility, possible remedies, and messaging strategies. Cluster analysis was used to determine attitudinal clusters. Participants were also able to qualify each answer. Qualitative responses were analysed both within and across attitudinal clusters using a constant comparative method. Three clusters were identified. Concerned Internalisers (27% of the sample) judged that obesity was a serious health problem, that Australia had among the highest levels of obesity in the world and that prevalence was rapidly increasing. They situated the causes and remedies for the obesity crisis in individual choices. Concerned Externalisers (38% of the sample) held similar views about the severity and extent of the obesity crisis. However, they saw responsibility and remedies as a societal rather than an individual issue. The final cluster, the Moderates, which contained significantly more children and males, believed that obesity was not such an important public health issue, and judged the extent of obesity to be less extreme than the other clusters

  7. ZnS nanoflakes deposition by modified chemical method

    International Nuclear Information System (INIS)

    Desai, Mangesh A.; Sartale, S. D.

    2014-01-01

    We report deposition of zinc sulfide nanoflakes on glass substrates by modified chemical method. The modified chemical method involves adsorption of zinc–thiourea complex on the substrate and its dissociation in presence of hydroxide ions to release sulfur ions from thiourea which react with zinc ions present in the complex to form zinc sulfide nanoflakes at room temperature. Influence of zinc salt and thiourea concentrations ratios on the morphology of the films was investigated by scanning electron microscope (SEM). The ratio of zinc and thiourea in the zinc–thiourea complex significantly affect the size of the zinc sulfide nanoflakes, especially width and density of the nanoflakes. The X-ray diffraction analysis exhibits polycrystalline nature of the zinc sulfide nanoflakes with hexagonal phase

  8. Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method

    DEFF Research Database (Denmark)

    Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

    2014-01-01

    The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probabi......The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models...... the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace...... method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous...

  9. Magnetism, structure and chemical order in small CoPd clusters: A first-principles study

    Energy Technology Data Exchange (ETDEWEB)

    Mokkath, Junais Habeeb, E-mail: Junais.Mokkath@kaust.edu.sa

    2014-01-15

    The structural, electronic and magnetic properties of small Co{sub m}Pd{sub n}(N=m+n=8,m=0−N) nanoalloy clusters are studied in the framework of a generalized-gradient approximation to density-functional theory. The optimized cluster structures have a clear tendency to maximize the number of nearest-neighbor CoCo pairs. The magnetic order is found to be ferromagnetic-like (FM) for all the ground-state structures. Antiferromagnetic-like spin arrangements were found in some low-lying isomers. The average magnetic moment per atom μ{sup ¯}{sub N} increases approximately linearly with Co content. A remarkable enhancement of the local Co moments is observed as a result of Pd doping. This is a consequence of the increase in the number of Co d holes, due to CoPd charge transfer, combined with the reduced local coordination. The influence of spin–orbit interactions on the cluster properties is also discussed. - Highlights: • This work analyses the structural and magnetic properties of CoPd nanoclusters. • The magnetic order is found to be ferromagnetic-like for all the ground-state structures. • The average magnetic moment per atom increases approximately linearly with Co content. • The influence of spin–orbit interactions on the cluster properties is discussed.

  10. Method and apparatus for controlling gas evolution from chemical reactions

    Science.gov (United States)

    Skorpik, James R.; Dodson, Michael G.

    1999-01-01

    The present invention is directed toward monitoring a thermally driven gas evolving chemical reaction with an acoustic apparatus. Signals from the acoustic apparatus are used to control a heater to prevent a run-away condition. A digestion module in combination with a robotic arm further automate physical handling of sample material reaction vessels. The invention is especially useful for carrying out sample procedures defined in EPA Methods SW-846.

  11. Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

    Science.gov (United States)

    Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

    2017-07-01

    One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

  12. A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data

    DEFF Research Database (Denmark)

    Kent, Peter; Jensen, Rikke K; Kongsted, Alice

    2014-01-01

    ). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold...... LCA and SNOB LCA). METHODS: The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program...... classify individuals into those subgroups. CONCLUSIONS: Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data...

  13. A method to determine the number of nanoparticles in a cluster using conventional optical microscopes

    International Nuclear Information System (INIS)

    Kang, Hyeonggon; Attota, Ravikiran; Tondare, Vipin; Vladár, András E.; Kavuri, Premsagar

    2015-01-01

    We present a method that uses conventional optical microscopes to determine the number of nanoparticles in a cluster, which is typically not possible using traditional image-based optical methods due to the diffraction limit. The method, called through-focus scanning optical microscopy (TSOM), uses a series of optical images taken at varying focus levels to achieve this. The optical images cannot directly resolve the individual nanoparticles, but contain information related to the number of particles. The TSOM method makes use of this information to determine the number of nanoparticles in a cluster. Initial good agreement between the simulations and the measurements is also presented. The TSOM method can be applied to fluorescent and non-fluorescent as well as metallic and non-metallic nano-scale materials, including soft materials, making it attractive for tag-less, high-speed, optical analysis of nanoparticles down to 45 nm diameter

  14. Study on magnetite nanoparticles synthesized by chemical method

    International Nuclear Information System (INIS)

    Pei Wenli; Kumada, H.; Natusme, T.; Saito, H.; Ishio, S.

    2007-01-01

    Magnetite nanoparticles with controlled size were synthesized by chemical method. Higher deposition temperature and a rapid-raising temperature procedure are favorable to particle size distribution and fabrication of monodisperse nanoparticles. The larger nanoparticles can be synthesized by the two-step method. The large nanoparticle (up to 25 nm) without agglomeration was successfully produced. The saturation magnetization of 11 nm magnetite particles was 45 emu/g at room temperature, which is smaller than that of bulk magnetite due to surface effect. Hysteresis of the magnetite nanoparticle was very small, indicating superparamagnetic behavior. The magnetic domains of the 11 nm magnetite nanoparticles were successfully observed by MFM

  15. Clustering method to process signals from a CdZnTe detector

    International Nuclear Information System (INIS)

    Zhang, Lan; Takahashi, Hiroyuki; Fukuda, Daiji; Nakazawa, Masaharu

    2001-01-01

    The poor mobility of holes in a compound semiconductor detector results in the imperfect collection of the primary charge deposited in the detector. Furthermore the fluctuation of the charge loss efficiency due to the change in the hole collection path length seriously degrades the energy resolution of the detector. Since the charge collection efficiency varies with the signal waveform, we can expect the improvement of the energy resolution through a proper waveform signal processing method. We developed a new digital signal processing technique, a clustering method which derives typical patterns containing the information on the real situation inside a detector from measured signals. The obtained typical patterns for the detector are then used for the pattern matching method. Measured signals are classified through analyzing the practical waveform variation due to the charge trapping, the electric field and the crystal defect etc. Signals with similar shape are placed into the same cluster. For each cluster we calculate an average waveform as a reference pattern. Using these reference patterns obtained from all the clusters, we can classify other measured signal waveforms from the same detector. Then signals are independently processed according to the classified category and form corresponding spectra. Finally these spectra are merged into one spectrum by multiplying normalization coefficients. The effectiveness of this method was verified with a CdZnTe detector of 2 mm thick and a 137 Cs gamma-ray source. The obtained energy resolution as improved to about 8 keV (FWHM). Because the clustering method is only related to the measured waveforms, it can be applied to any type and size of detectors and compatible with any type of filtering methods. (author)

  16. Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

    Directory of Open Access Journals (Sweden)

    Lee Yun-Shien

    2008-03-01

    Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

  17. Statistical method on nonrandom clustering with application to somatic mutations in cancer

    Directory of Open Access Journals (Sweden)

    Rejto Paul A

    2010-01-01

    Full Text Available Abstract Background Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention. Results We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and β-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors. Conclusions Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.

  18. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations

    International Nuclear Information System (INIS)

    Wu, Fuke; Tian, Tianhai; Rawlings, James B.; Yin, George

    2016-01-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766–1793 (1996); ibid. 56, 1794–1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.

  19. Annotated Computer Output for Illustrative Examples of Clustering Using the Mixture Method and Two Comparable Methods from SAS.

    Science.gov (United States)

    1987-06-26

    BUREAU OF STANDAR-S1963-A Nw BOM -ILE COPY -. 4eo .?3sa.9"-,,A WIN* MAT HEMATICAL SCIENCES _*INSTITUTE AD-A184 687 DTICS!ELECTE ANNOTATED COMPUTER OUTPUT...intoduction to the use of mixture models in clustering. Cornell University Biometrics Unit Technical Report BU-920-M and Mathematical Sciences Institute...mixture method and two comparable methods from SAS. Cornell University Biometrics Unit Technical Report BU-921-M and Mathematical Sciences Institute

  20. CHEMICAL ABUNDANCE PATTERNS IN THE INNER GALAXY: THE SCUTUM RED SUPERGIANT CLUSTERS

    International Nuclear Information System (INIS)

    Davies, Ben; Origlia, Livia; Kudritzki, Rolf-Peter; Figer, Don F.; Rich, R. Michael; Najarro, Francisco; Negueruela, Ignacio; Clark, J. Simon

    2009-01-01

    The location of the Scutum Red Supergiant (RSG) clusters at the end of the Galactic Bar makes them an excellent probe of the Galaxy's secular evolution, while the clusters themselves are ideal testbeds in which to study the predictions of stellar evolutionary theory. To this end, we present a study of the RSG's surface abundances using a combination of high-resolution Keck/NIRSPEC H-band spectroscopy and spectral synthesis analysis. We provide abundance measurements for elements C, O, Si, Mg, Ti, and Fe. We find that the surface abundances of the stars studied are consistent with CNO burning and deep, rotationally enhanced mixing. The average α/Fe ratios of the clusters are solar, consistent with a thin-disk population. However, we find significantly subsolar Fe/H ratios for each cluster, a result which strongly contradicts a simple extrapolation of the Galactic metallicity gradient to lower Galactocentric distances. We suggest that a simple one-dimensional parameterization of the Galaxy's abundance patterns is insufficient at low Galactocentric distances, as large azimuthal variations may be present. Indeed, we show that the abundances of O, Si, and Mg are consistent with independent measurements of objects in similar locations in the Galaxy. In combining our results with other data in the literature, we present evidence for large-scale (∼ kpc) azimuthal variations in abundances at Galactocentric distances of 3-5 kpc. While we cannot rule out that this observed behavior is due to systematic offsets between different measurement techniques, we do find evidence for similar behavior in a study of the barred spiral galaxy NGC 4736 which uses homogeneous methodology. We suggest that these azimuthal abundance variations could result from the intense but patchy star formation driven by the potential of the central bar.

  1. Cluster-cluster clustering

    International Nuclear Information System (INIS)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

    1985-01-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

  2. Research of the Space Clustering Method for the Airport Noise Data Minings

    Directory of Open Access Journals (Sweden)

    Jiwen Xie

    2014-03-01

    Full Text Available Mining the distribution pattern and evolution of the airport noise from the airport noise data and the geographic information of the monitoring points is of great significance for the scientific and rational governance of airport noise pollution problem. However, most of the traditional clustering methods are based on the closeness of space location or the similarity of non-spatial features, which split the duality of space elements, resulting in that the clustering result has difficult in satisfying both the closeness of space location and the similarity of non-spatial features. This paper, therefore, proposes a spatial clustering algorithm based on dual-distance. This algorithm uses a distance function as the similarity measure function in which spatial features and non-spatial features are combined. The experimental results show that the proposed algorithm can discover the noise distribution pattern around the airport effectively.

  3. Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

    KAUST Repository

    Elsheikh, Ahmed H.

    2013-05-01

    A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.

  4. Chemical abundances of giant stars in NGC 5053 and NGC 5634, two globular clusters associated with the Sagittarius dwarf spheroidal galaxy?

    Science.gov (United States)

    Sbordone, L.; Monaco, L.; Moni Bidin, C.; Bonifacio, P.; Villanova, S.; Bellazzini, M.; Ibata, R.; Chiba, M.; Geisler, D.; Caffau, E.; Duffau, S.

    2015-07-01

    Context. The tidal disruption of the Sagittarius dwarf spheroidal galaxy (Sgr dSph) is producing the most prominent substructure in the Milky Way (MW) halo, the Sagittarius Stream. Aside from field stars, it is suspected that the Sgr dSph has lost a number of globular clusters (GC). Many Galactic GC are thought to have originated in the Sgr dSph. While for some candidates an origin in the Sgr dSph has been confirmed owing to chemical similarities, others exist whose chemical composition has never been investigated. Aims: NGC 5053 and NGC 5634 are two of these scarcely studied Sgr dSph candidate-member clusters. To characterize their composition we analyzed one giant star in NGC 5053, and two in NGC 5634. Methods: We analyze high-resolution and signal-to-noise spectra by means of the MyGIsFOS code, determining atmospheric parameters and abundances for up to 21 species between O and Eu. The abundances are compared with those of MW halo field stars, of unassociated MW halo globulars, and of the metal-poor Sgr dSph main body population. Results: We derive a metallicity of [Fe ii/H] = -2.26 ± 0.10 for NGC 5053, and of [Fe i/H] = -1.99 ± 0.075 and -1.97 ± 0.076 for the two stars in NGC 5634. This makes NGC 5053 one of the most metal-poor globular clusters in the MW. Both clusters display an α enhancement similar to the one of the halo at comparable metallicity. The two stars in NGC 5634 clearly display the Na-O anticorrelation widespread among MW globulars. Most other abundances are in good agreement with standard MW halo trends. Conclusions: The chemistry of the Sgr dSph main body populations is similar to that of the halo at low metallicity. It is thus difficult to discriminate between an origin of NGC 5053 and NGC 5634 in the Sgr dSph, and one in the MW. However, the abundances of these clusters do appear closer to that of Sgr dSph than of the halo, favoring an origin in the Sgr dSph system. Appendix A is available in electronic form at http

  5. Implementation of K-Means Clustering Method for Electronic Learning Model

    Science.gov (United States)

    Latipa Sari, Herlina; Suranti Mrs., Dewi; Natalia Zulita, Leni

    2017-12-01

    Teaching and Learning process at SMK Negeri 2 Bengkulu Tengah has applied e-learning system for teachers and students. The e-learning was based on the classification of normative, productive, and adaptive subjects. SMK Negeri 2 Bengkulu Tengah consisted of 394 students and 60 teachers with 16 subjects. The record of e-learning database was used in this research to observe students’ activity pattern in attending class. K-Means algorithm in this research was used to classify students’ learning activities using e-learning, so that it was obtained cluster of students’ activity and improvement of student’s ability. Implementation of K-Means Clustering method for electronic learning model at SMK Negeri 2 Bengkulu Tengah was conducted by observing 10 students’ activities, namely participation of students in the classroom, submit assignment, view assignment, add discussion, view discussion, add comment, download course materials, view article, view test, and submit test. In the e-learning model, the testing was conducted toward 10 students that yielded 2 clusters of membership data (C1 and C2). Cluster 1: with membership percentage of 70% and it consisted of 6 members, namely 1112438 Anggi Julian, 1112439 Anis Maulita, 1112441 Ardi Febriansyah, 1112452 Berlian Sinurat, 1112460 Dewi Anugrah Anwar and 1112467 Eka Tri Oktavia Sari. Cluster 2:with membership percentage of 30% and it consisted of 4 members, namely 1112463 Dosita Afriyani, 1112471 Erda Novita, 1112474 Eskardi and 1112477 Fachrur Rozi.

  6. Study of methods to increase cluster/dislocation loop densities in electrodes

    Science.gov (United States)

    Yang, Xiaoling; Miley, George H.

    2009-03-01

    Recent research has developed a technique for imbedding ultra-high density deuterium ``clusters'' (50 to 100 atoms per cluster) in various metals such as Palladium (Pd), Beryllium (Be) and Lithium (Li). It was found the thermally dehydrogenated PdHx retained the clusters and exhibited up to 12 percent lower resistance compared to the virginal Pd samplesootnotetextA. G. Lipson, et al. Phys. Solid State. 39 (1997) 1891. SQUID measurements showed that in Pd these condensed matter clusters approach metallic conditions, exhibiting superconducting propertiesootnotetextA. Lipson, et al. Phys. Rev. B 72, 212507 (2005ootnotetextA. G. Lipson, et al. Phys. Lett. A 339, (2005) 414-423. If the fabrication methods under study are successful, a large packing fraction of nuclear reactive clusters can be developed in the electrodes by electrolyte or high pressure gas loading. This will provide a much higher low-energy-nuclear- reaction (LENR) rate than achieved with earlier electrodeootnotetextCastano, C.H., et al. Proc. ICCF-9, Beijing, China 19-24 May, 2002..

  7. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments

    Directory of Open Access Journals (Sweden)

    Wen Liu

    2016-12-01

    Full Text Available Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS. Due to the absence of satellite signal in Global Navigation Satellite System (GNSS, various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP, which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC, is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1 and the XiDan Joy City (Floors 1 and 2, as Test-bed 2, and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  8. Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments.

    Science.gov (United States)

    Liu, Wen; Fu, Xiao; Deng, Zhongliang

    2016-12-02

    Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

  9. Magnetism, structure and chemical order in small CoPd clusters: A first-principles study

    KAUST Repository

    Mokkath, Junais Habeeb

    2014-01-01

    The structural, electronic and magnetic properties of small ComPdn (N=m+n=8,m=0-N) nanoalloy clusters are studied in the framework of a generalized-gradient approximation to density-functional theory. The optimized cluster structures have a clear tendency to maximize the number of nearest-neighbor CoCo pairs. The magnetic order is found to be ferromagnetic-like (FM) for all the ground-state structures. Antiferromagnetic-like spin arrangements were found in some low-lying isomers. The average magnetic moment per atom μ̄N increases approximately linearly with Co content. A remarkable enhancement of the local Co moments is observed as a result of Pd doping. This is a consequence of the increase in the number of Co d holes, due to CoPd charge transfer, combined with the reduced local coordination. The influence of spin-orbit interactions on the cluster properties is also discussed. © 2013 Elsevier B.V.

  10. IP2P K-means: an efficient method for data clustering on sensor networks

    Directory of Open Access Journals (Sweden)

    Peyman Mirhadi

    2013-03-01

    Full Text Available Many wireless sensor network applications require data gathering as the most important parts of their operations. There are increasing demands for innovative methods to improve energy efficiency and to prolong the network lifetime. Clustering is considered as an efficient topology control methods in wireless sensor networks, which can increase network scalability and lifetime. This paper presents a method, IP2P K-means – Improved P2P K-means, which uses efficient leveling in clustering approach, reduces false labeling and restricts the necessary communication among various sensors, which obviously saves more energy. The proposed method is examined in Network Simulator Ver.2 (NS2 and the preliminary results show that the algorithm works effectively and relatively more precisely.

  11. Investigation of chemical equilibrium kinetics by the electromigration method

    International Nuclear Information System (INIS)

    Bozhikov, G.A.; Ivanov, P.I.; Maslov, O.D.; Dmitriev, S.N.; Bontchev, G.D.; Milanov, M.V.

    2003-01-01

    The measurement of the chemical reaction rates for complex formation as well as hydrolysis type reactions by the method of horizontal zone electrophoresis is outlined. The correlation between chemical equilibrium kinetics and electrodiffusion processes in a constant d.c. electric field is described. In model electromigration experiments the reaction rate constant of the formation a complex by Hf(IV) and diethylenetriaminepentaacetic acid (DTPA) is determined. The electrophoretic mobility, diffusion coefficient and stability constant of the [HfDTPA] - complex are calculated, taking into account experimental electrophoretic data obtained at 298.15±0.05 K and constant ionic strength. No-carrier-added 175 Hf radionuclide was used in electromigration experiments at concentrations of 10 -10 -10 -11 M. (orig.)

  12. Method for Determining Appropriate Clustering Criteria of Location-Sensing Data

    Directory of Open Access Journals (Sweden)

    Youngmin Lee

    2016-08-01

    Full Text Available Large quantities of location-sensing data are generated from location-based social network services. These data are provided as point properties with location coordinates acquired from a global positioning system or Wi-Fi signal. To show the point data on multi-scale map services, the data should be represented by clusters following a grid-based clustering method, in which an appropriate grid size should be determined. Currently, there are no criteria for determining the proper grid size, and the modifiable areal unit problem has been formulated for the purpose of addressing this issue. The method proposed in this paper is applies a hexagonal grid to geotagged Twitter point data, considering the grid size in terms of both quantity and quality to minimize the limitations associated with the modifiable areal unit problem. Quantitatively, we reduced the original Twitter point data by an appropriate amount using Töpfer’s radical law. Qualitatively, we maintained the original distribution characteristics using Moran’s I. Finally, we determined the appropriate sizes of clusters from zoom levels 9–13 by analyzing the distribution of data on the graphs. Based on the visualized clustering results, we confirm that the original distribution pattern is effectively maintained using the proposed method.

  13. Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K.; /Stockholm U. /SLAC

    2005-08-05

    We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.

  14. Structure and bonding in clusters

    International Nuclear Information System (INIS)

    Kumar, V.

    1991-10-01

    We review here the recent progress made in the understanding of the electronic and atomic structure of small clusters of s-p bonded materials using the density functional molecular dynamics technique within the local density approximation. Starting with a brief description of the method, results are presented for alkali metal clusters, clusters of divalent metals such as Mg and Be which show a transition from van der Waals or weak chemical bonding to metallic behaviour as the cluster size grows and clusters of Al, Sn and Sb. In the case of semiconductors, we discuss results for Si, Ge and GaAs clusters. Clusters of other materials such as P, C, S, and Se are also briefly discussed. From these and other available results we suggest the possibility of unique structures for the magic clusters. (author). 69 refs, 7 figs, 1 tab

  15. Relativistic rise measurement by cluster counting method in time expansion chamber

    International Nuclear Information System (INIS)

    Rehak, P.; Walenta, A.H.

    1979-10-01

    A new approach to the measurement of the ionization energy loss for the charged particle identification in the region of the relativistic rise was tested experimentally. The method consists of determining in a special drift chamber (TEC) the number of clusters of the primary ionization. The method gives almost the full relativistic rise and narrower landau distribution. The consequences for a practical detector are discussed

  16. Stepwise threshold clustering: a new method for genotyping MHC loci using next-generation sequencing technology.

    Directory of Open Access Journals (Sweden)

    William E Stutz

    Full Text Available Genes of the vertebrate major histocompatibility complex (MHC are of great interest to biologists because of their important role in immunity and disease, and their extremely high levels of genetic diversity. Next generation sequencing (NGS technologies are quickly becoming the method of choice for high-throughput genotyping of multi-locus templates like MHC in non-model organisms. Previous approaches to genotyping MHC genes using NGS technologies suffer from two problems:1 a "gray zone" where low frequency alleles and high frequency artifacts can be difficult to disentangle and 2 a similar sequence problem, where very similar alleles can be difficult to distinguish as two distinct alleles. Here were present a new method for genotyping MHC loci--Stepwise Threshold Clustering (STC--that addresses these problems by taking full advantage of the increase in sequence data provided by NGS technologies. Unlike previous approaches for genotyping MHC with NGS data that attempt to classify individual sequences as alleles or artifacts, STC uses a quasi-Dirichlet clustering algorithm to cluster similar sequences at increasing levels of sequence similarity. By applying frequency and similarity based criteria to clusters rather than individual sequences, STC is able to successfully identify clusters of sequences that correspond to individual or similar alleles present in the genomes of individual samples. Furthermore, STC does not require duplicate runs of all samples, increasing the number of samples that can be genotyped in a given project. We show how the STC method works using a single sample library. We then apply STC to 295 threespine stickleback (Gasterosteus aculeatus samples from four populations and show that neighboring populations differ significantly in MHC allele pools. We show that STC is a reliable, accurate, efficient, and flexible method for genotyping MHC that will be of use to biologists interested in a variety of downstream applications.

  17. An experimental design method leading to chemical Turing patterns.

    Science.gov (United States)

    Horváth, Judit; Szalai, István; De Kepper, Patrick

    2009-05-08

    Chemical reaction-diffusion patterns often serve as prototypes for pattern formation in living systems, but only two isothermal single-phase reaction systems have produced sustained stationary reaction-diffusion patterns so far. We designed an experimental method to search for additional systems on the basis of three steps: (i) generate spatial bistability by operating autoactivated reactions in open spatial reactors; (ii) use an independent negative-feedback species to produce spatiotemporal oscillations; and (iii) induce a space-scale separation of the activatory and inhibitory processes with a low-mobility complexing agent. We successfully applied this method to a hydrogen-ion autoactivated reaction, the thiourea-iodate-sulfite (TuIS) reaction, and noticeably produced stationary hexagonal arrays of spots and parallel stripes of pH patterns attributed to a Turing bifurcation. This method could be extended to biochemical reactions.

  18. A method of refining aromatic hydrocarbons from coal chemical production

    Energy Technology Data Exchange (ETDEWEB)

    Zieborak, K.; Koprowski, A.; Ratajczak, W.

    1979-10-01

    A method is disclosed for refining aromatic hydrocarbons of coal chemical production by contact of liquid aromatic hydrocarbons and their mixtures with a strongly acid macroporous sulfocationite in the H-form at atmospheric pressure and high temperature. The method is distinguished in that the aromatic hydrocarbons and their mixtures, from which alkali compounds have already been removed, are supplied for refinement with the sulfocationite with simultaneous addition of olefin derivatives of aromatic hydrocarbons, followed by separation of pure hydrocarbons by rectification. Styrene or alpha-methylstyrene is used as the olefin derivatives of the aromatic hydrocarbons. The method is performed in several stages with addition of olefin derivatives of aromatic hydrocarbons at each stage.

  19. a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

    Science.gov (United States)

    Huang, W.; Li, S.; Xu, S.

    2016-06-01

    How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the

  20. A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Huang

    2016-06-01

    Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

  1. Methods of chemical and phase composition analysis of gallstones

    Science.gov (United States)

    Suvorova, E. I.; Pantushev, V. V.; Voloshin, A. E.

    2017-11-01

    This review presents the instrumental methods used for chemical and phase composition investigation of gallstones. A great body of data has been collected in the literature on the presence of elements and their concentrations, obtained by fluorescence microscopy, X-ray fluorescence spectroscopy, neutron activation analysis, proton (particle) induced X-ray emission, atomic absorption spectroscopy, high-resolution gamma-ray spectrometry, electron paramagnetic resonance. Structural methods—powder X-ray diffraction, infrared spectroscopy, Raman spectroscopy—provide information about organic and inorganic phases in gallstones. Stone morphology was studied at the macrolevel with optical microscopy. Results obtained by analytical scanning and transmission electron microscopy with X-ray energy dispersive spectrometry are discussed. The chemical composition and structure of gallstones determine the strategy of removing stone from the body and treatment of patients: surgery or dissolution in the body. Therefore one chapter of the review describes the potential of dissolution methods. Early diagnosis and appropriate treatment of the disease depend on the development of clinical methods for in vivo investigation, which gave grounds to present the main characteristics and potential of ultrasonography (ultrasound scanning), magnetic resonance imaging, and X-ray computed tomography.

  2. Pre-crash scenarios at road junctions: A clustering method for car crash data.

    Science.gov (United States)

    Nitsche, Philippe; Thomas, Pete; Stuetz, Rainer; Welsh, Ruth

    2017-10-01

    Given the recent advancements in autonomous driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual simulation environments or on real-world test tracks. This paper presents a novel data analysis method including the preparation, analysis and visualization of car crash data, to identify the critical pre-crash scenarios at T- and four-legged junctions as a basis for testing the safety of automated driving systems. The presented method employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1056 junction crashes in the UK, which were exported from the in-depth "On-the-Spot" database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions. The results support existing findings on road junction accidents and provide benchmark situations for safety performance tests in order to reduce the possible number parameter combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.

    Science.gov (United States)

    Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong

    2017-02-28

    The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.

  4. An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

    Directory of Open Access Journals (Sweden)

    Deepa Devasenapathy

    2015-01-01

    Full Text Available The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  5. An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

    Science.gov (United States)

    Devasenapathy, Deepa; Kannan, Kathiravan

    2015-01-01

    The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

  6. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  7. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  8. Water Quality Evaluation of the Yellow River Basin Based on Gray Clustering Method

    Science.gov (United States)

    Fu, X. Q.; Zou, Z. H.

    2018-03-01

    Evaluating the water quality of 12 monitoring sections in the Yellow River Basin comprehensively by grey clustering method based on the water quality monitoring data from the Ministry of environmental protection of China in May 2016 and the environmental quality standard of surface water. The results can reflect the water quality of the Yellow River Basin objectively. Furthermore, the evaluation results are basically the same when compared with the fuzzy comprehensive evaluation method. The results also show that the overall water quality of the Yellow River Basin is good and coincident with the actual situation of the Yellow River basin. Overall, gray clustering method for water quality evaluation is reasonable and feasible and it is also convenient to calculate.

  9. AN ANALYTICAL METHOD FOR CHEMICAL SPECIATION OF SELENIUM IN SOIL

    Directory of Open Access Journals (Sweden)

    Constantin Luca

    2010-10-01

    Full Text Available Selenium is an essential microelement, sometimes redoubtable, through its beneficial role - risk depending on its concentration in the food chain, at low dose is an important nutrient in the life of humans and animals, contrary at high doses, it becomes toxic. Selenium may be find itself in the environment (soil, sediment, water in many forms (oxidized, reduced, organometallic which determine their mobility and toxicity. Determination of chemical speciation (identification of different chemical forms provides much more complete information for a better understanding of the behavior and the potential impact on the environment. In this work we present the results of methodological research on the extraction of sequential forms of selenium in the soil and the coupling of analytical methods capable of identifying very small amounts of selenium in soils An efficient scheme of sequential extractions forms of selenium (SES consisting in atomic absorption spectrometry coupled with hydride generation (HGAAS has been developed into five experimental steps, detailed in the paper. This operational scheme has been applied to the analysis of chemical speciation in the following areas: the Bărăgan Plain and Central Dobrogea of Romania.

  10. Use of ab initio quantum chemical methods in battery technology

    Energy Technology Data Exchange (ETDEWEB)

    Deiss, E [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1997-06-01

    Ab initio quantum chemistry can nowadays predict physical and chemical properties of molecules and solids. An attempt should be made to use this tool more widely for predicting technologically favourable materials. To demonstrate the use of ab initio quantum chemistry in battery technology, the theoretical energy density (energy per volume of active electrode material) and specific energy (energy per mass of active electrode material) of a rechargeable lithium-ion battery consisting of a graphite electrode and a nickel oxide electrode has been calculated with this method. (author) 1 fig., 1 tab., 7 refs.

  11. Synthesis of Lead Sulfide Nanoparticles by Chemical Precipitation Method

    International Nuclear Information System (INIS)

    Chongad, L S; Sharma, A; Banerjee, M; Jain, A

    2016-01-01

    Lead sulfide (PbS) nanoparticles were prepared by chemical precipitation method (CPM) with the assistance of H 2 S gas. The microstructure and morphology of the synthesized nanoparticles have been investigated using X-ray diffraction (XRD) and transmission electron microscopy (TEM). The XRD patterns of the PbS nanoparticles reveal formation of cubic phase. To investigate the quality of prepared nanoparticles, the particles size, lattice constant, strain, dislocation density etc. have been determined using XRD. TEM images reveal formation of cubic nanoparticles and the particle size determined from TEM images agree well with those from XRD. (paper)

  12. Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

    Science.gov (United States)

    Karaca, Yeliz; Cattani, Carlo

    Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

  13. Threshold selection for classification of MR brain images by clustering method

    Energy Technology Data Exchange (ETDEWEB)

    Moldovanu, Simona [Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, Dunărea de Jos University of Galaţi, 47 Domnească St., 800008, Romania, Phone: +40 236 460 780 (Romania); Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi (Romania); Obreja, Cristian; Moraru, Luminita, E-mail: luminita.moraru@ugal.ro [Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, Dunărea de Jos University of Galaţi, 47 Domnească St., 800008, Romania, Phone: +40 236 460 780 (Romania)

    2015-12-07

    Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

  14. Alternative Chemical Amplification Methods for Peroxy Radical Detection

    Science.gov (United States)

    Wood, E. C. D.

    2014-12-01

    Peroxy radicals (HO2, CH3O2, etc.) are commonly detected by the chemical amplification technique, in which ambient air is mixed with high concentrations of CO and NO, initiating a chain reaction that produces 30 - 200 NO2 molecules per sampled peroxy radical. The NO2 is then measured by one of several techniques. With the exception of CIMS-based techniques, the chemical amplification method has undergone only incremental improvements since it was first introduced in 1982. The disadvantages of the technique include the need to use high concentrations of CO and the greatly reduced sensitivity of the amplification chain length in the presence of water vapor. We present a new chemical amplification scheme in which either ethane or acetaldehyde is used in place of CO, with the NO2 product detected using Cavity Attenuated Phase Shift spectroscopy (CAPS). Under dry conditions, the amplification factor of the alternative amplifiers are approximately six times lower than the CO-based amplifier. The relative humidity "penalty" is not as severe, however, such that at typical ambient relative humidity (RH) values the amplification factor is within a factor of three of the CO-based amplifier. Combined with the NO2 sensitivity of CAPS and a dual-channel design, the detection limit of the ethane amplifier is less than 2 ppt (1 minute average, signal-to-noise ratio 2). The advantages of these alternative chemical amplification schemes are improved safety, a reduced RH correction, and increased sensitivity to organic peroxy radicals relative to HO2.

  15. Finite Size Effects in Chemical Bonding: From Small Clusters to Solids

    DEFF Research Database (Denmark)

    Kleis, Jesper; Greeley, Jeffrey Philip; Romero, N. A.

    2011-01-01

    We address the fundamental question of which size a metallic nano-particle needs to have before its surface chemical properties can be considered to be those of a solid, rather than those of a large molecule. Calculations of adsorption energies for carbon monoxide and oxygen on a series of gold...

  16. Chemical composition of the horizontal-branch stars of globular clusters in the galactic field

    International Nuclear Information System (INIS)

    Klochkova, V.G.; Panchuk, V.E.

    1987-01-01

    Chemical abundance is calculated for 6 field stars: HD 2857, 64488, 93329, 105262, HDE 281679, BD+20 deg 5009, using 12 spectra with a reciprocal dispersion of 9 A/mm, obtained on the 6-m telescope. Fundamental characteristics for 7 stars of the horizontal branch are found

  17. Symmetrized partial-wave method for density-functional cluster calculations

    International Nuclear Information System (INIS)

    Averill, F.W.; Painter, G.S.

    1994-01-01

    The computational advantage and accuracy of the Harris method is linked to the simplicity and adequacy of the reference-density model. In an earlier paper, we investigated one way the Harris functional could be extended to systems outside the limits of weakly interacting atoms by making the charge density of the interacting atoms self-consistent within the constraints of overlapping spherical atomic densities. In the present study, a method is presented for augmenting the interacting atom charge densities with symmetrized partial-wave expansions on each atomic site. The added variational freedom of the partial waves leads to a scheme capable of giving exact results within a given exchange-correlation approximation while maintaining many of the desirable convergence and stability properties of the original Harris method. Incorporation of the symmetry of the cluster in the partial-wave construction further reduces the level of computational effort. This partial-wave cluster method is illustrated by its application to the dimer C 2 , the hypothetical atomic cluster Fe 6 Al 8 , and the benzene molecule

  18. Cluster detection methods applied to the Upper Cape Cod cancer data

    Directory of Open Access Journals (Sweden)

    Ozonoff David

    2005-09-01

    Full Text Available Abstract Background A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. Methods We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. Results The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. Conclusion The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.

  19. Chemical methods for the determination of composition of cryolite

    International Nuclear Information System (INIS)

    Shivarudrappa, V.; Patil, B.N.; Marathe, S.G.; Jain, H.C.

    1989-01-01

    Preparation of uranium and plutonium alloys containing aluminium involves the use of cryolite and many times, cryolite which may be contaminated with alpha activity has to be analysed for its purity. In view of this, chemical methods for the determination of composition of commercial cryolite samples have been developed. Methods are standardised for the determination of individual constituents of cryolite viz., aluminium, sodium, fluoride and major impurities, calcium and magnesium. Studies on the dissolution of the sample, effect of one or more components on the determination of the other and their elimination are carried out. Aluminium and sodium are determined gravimetrically as oxinate and triple acetate respectively. Fluoride is determined by a volumetric procedure after cation exchange separtion of soluble fluoride. Calcium and magnesium are determined by a sequential pH-metri titration. This report describes the details of the procedures and the results of these studies for two commercial cryolite samples. (author). 7 tabs

  20. Atypical Mg-poor Milky Way Field Stars with Globular Cluster Second-generation-like Chemical Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Fernández-Trincado, J. G.; Geisler, D.; Tang, B.; Villanova, S.; Mennickent, R. E. [Departamento de Astronomía, Universidad de Concepción, Casilla 160-C, Concepción (Chile); Zamora, O.; García-Hernández, D. A.; Dell’Agli, F.; Prieto, Carlos Allende [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Souto, Diogo; Cunha, Katia [Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ—20921-400 (Brazil); Schiavon, R. P. [Astrophysics Research Institute, Liverpool John Moores University, 146 Brownlow Hill, Liverpool L3 5RF (United Kingdom); Hasselquist, Sten [New Mexico State University, Las Cruces, NM 88003 (United States); Shetrone, M. [University of Texas at Austin, McDonald Observatory, Fort Davis, TX 79734 (United States); Vieira, K. [Centro de Investigaciones de Astronomía, AP 264, Mérida 5101-A (Venezuela, Bolivarian Republic of); Zasowski, G. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Sobeck, J.; Hayes, C. R.; Majewski, S. R. [Department of Astronomy, University of Virginia, Charlottesville, VA 22903 (United States); Placco, V. M., E-mail: jfernandezt@astro-udec.cl, E-mail: jfernandezt87@gmail.com [Department of Physics and JINA Center for the Evolution of the Elements, University of Notre Dame, Notre Dame, IN 46556 (United States); and others

    2017-09-01

    We report the peculiar chemical abundance patterns of 11 atypical Milky Way (MW) field red giant stars observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE). These atypical giants exhibit strong Al and N enhancements accompanied by C and Mg depletions, strikingly similar to those observed in the so-called second-generation (SG) stars of globular clusters (GCs). Remarkably, we find low Mg abundances ([Mg/Fe] < 0.0) together with strong Al and N overabundances in the majority (5/7) of the metal-rich ([Fe/H] ≳ −1.0) sample stars, which is at odds with actual observations of SG stars in Galactic GCs of similar metallicities. This chemical pattern is unique and unprecedented among MW stars, posing urgent questions about its origin. These atypical stars could be former SG stars of dissolved GCs formed with intrinsically lower abundances of Mg and enriched Al (subsequently self-polluted by massive AGB stars) or the result of exotic binary systems. We speculate that the stars Mg-deficiency as well as the orbital properties suggest that they could have an extragalactic origin. This discovery should guide future dedicated spectroscopic searches of atypical stellar chemical patterns in our Galaxy, a fundamental step forward to understanding the Galactic formation and evolution.

  1. Applying Clustering Methods in Drawing Maps of Science: Case Study of the Map For Urban Management Science

    Directory of Open Access Journals (Sweden)

    Mohammad Abuei Ardakan

    2010-04-01

    Full Text Available The present paper offers a basic introduction to data clustering and demonstrates the application of clustering methods in drawing maps of science. All approaches towards classification and clustering of information are briefly discussed. Their application to the process of visualization of conceptual information and drawing of science maps are illustrated by reviewing similar researches in this field. By implementing aggregated hierarchical clustering algorithm, which is an algorithm based on complete-link method, the map for urban management science as an emerging, interdisciplinary scientific field is analyzed and reviewed.

  2. Fourth-order perturbative extension of the single-double excitation coupled-cluster method

    International Nuclear Information System (INIS)

    Derevianko, Andrei; Emmons, Erik D.

    2002-01-01

    Fourth-order many-body corrections to matrix elements for atoms with one valence electron are derived. The obtained diagrams are classified using coupled-cluster-inspired separation into contributions from n-particle excitations from the lowest-order wave function. The complete set of fourth-order diagrams involves only connected single, double, and triple excitations and disconnected quadruple excitations. Approximately half of the fourth-order diagrams are not accounted for by the popular coupled-cluster method truncated at single and double excitations (CCSD). Explicit formulas are tabulated for the entire set of fourth-order diagrams missed by the CCSD method and its linearized version, i.e., contributions from connected triple and disconnected quadruple excitations. A partial summation scheme of the derived fourth-order contributions to all orders of perturbation theory is proposed

  3. Cluster models of light nuclei and the method of hyperspherical harmonics: Successes and challenges

    International Nuclear Information System (INIS)

    Danilin, B. V.; Shul'gina, N. B.; Ershov, S. N.; Vaagen, J. S.

    2009-01-01

    Hyperspherical-harmonics method to investigate the lightest nuclei having three-cluster structure is discussed together with recent experiments. Properties of bound states and methods to explore three-body continuum are presented. The challenges created by large neutron excess and halo phenomena are highlighted. Astrophysical aspects of the 7 Li + n → 8 Li + γ reaction and the solar-boron-neutrinos problem are analyzed. Three-cluster structure of highly excited states in 8 Be is shown to be responsible for extreme isospin mixing. Progress in studies of 6 He- and 11 Li-induced inclusive and exclusive nuclear reactions is demonstrated, providing information on the nature of continuum structures of Borromean nuclei.

  4. A New Waveform Signal Processing Method Based on Adaptive Clustering-Genetic Algorithms

    International Nuclear Information System (INIS)

    Noha Shaaban; Fukuzo Masuda; Hidetsugu Morota

    2006-01-01

    We present a fast digital signal processing method for numerical analysis of individual pulses from CdZnTe compound semiconductor detectors. Using Maxi-Mini Distance Algorithm and Genetic Algorithms based discrimination technique. A parametric approach has been used for classifying the discriminated waveforms into a set of clusters each has a similar signal shape with a corresponding pulse height spectrum. A corrected total pulse height spectrum was obtained by applying a normalization factor for the full energy peak for each cluster with a highly improvements in the energy spectrum characteristics. This method applied successfully for both simulated and real measured data, it can be applied to any detector suffers from signal shape variation. (authors)

  5. The IMACS Cluster Building Survey. I. Description of the Survey and Analysis Methods

    Science.gov (United States)

    Oemler Jr., Augustus; Dressler, Alan; Gladders, Michael G.; Rigby, Jane R.; Bai, Lei; Kelson, Daniel; Villanueva, Edward; Fritz, Jacopo; Rieke, George; Poggianti, Bianca M.; hide

    2013-01-01

    The IMACS Cluster Building Survey uses the wide field spectroscopic capabilities of the IMACS spectrograph on the 6.5 m Baade Telescope to survey the large-scale environment surrounding rich intermediate-redshift clusters of galaxies. The goal is to understand the processes which may be transforming star-forming field galaxies into quiescent cluster members as groups and individual galaxies fall into the cluster from the surrounding supercluster. This first paper describes the survey: the data taking and reduction methods. We provide new calibrations of star formation rates (SFRs) derived from optical and infrared spectroscopy and photometry. We demonstrate that there is a tight relation between the observed SFR per unit B luminosity, and the ratio of the extinctions of the stellar continuum and the optical emission lines.With this, we can obtain accurate extinction-corrected colors of galaxies. Using these colors as well as other spectral measures, we determine new criteria for the existence of ongoing and recent starbursts in galaxies.

  6. THE IMACS CLUSTER BUILDING SURVEY. I. DESCRIPTION OF THE SURVEY AND ANALYSIS METHODS

    Energy Technology Data Exchange (ETDEWEB)

    Oemler, Augustus Jr.; Dressler, Alan; Kelson, Daniel; Villanueva, Edward [Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101-1292 (United States); Gladders, Michael G. [Department of Astronomy and Astrophysics, University of Chicago, Chicago, IL 60637 (United States); Rigby, Jane R. [Observational Cosmology Lab, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Bai Lei [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4 (Canada); Fritz, Jacopo [Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281 S9, B-9000 Gent (Belgium); Rieke, George [Steward Observatory, University of Arizona, Tucson, AZ 8572 (United States); Poggianti, Bianca M.; Vulcani, Benedetta, E-mail: oemler@obs.carnegiescience.edu [INAF-Osservatorio Astronomico di Padova, Vicolo dell' Osservatorio 5, I-35122 Padova (Italy)

    2013-06-10

    The IMACS Cluster Building Survey uses the wide field spectroscopic capabilities of the IMACS spectrograph on the 6.5 m Baade Telescope to survey the large-scale environment surrounding rich intermediate-redshift clusters of galaxies. The goal is to understand the processes which may be transforming star-forming field galaxies into quiescent cluster members as groups and individual galaxies fall into the cluster from the surrounding supercluster. This first paper describes the survey: the data taking and reduction methods. We provide new calibrations of star formation rates (SFRs) derived from optical and infrared spectroscopy and photometry. We demonstrate that there is a tight relation between the observed SFR per unit B luminosity, and the ratio of the extinctions of the stellar continuum and the optical emission lines. With this, we can obtain accurate extinction-corrected colors of galaxies. Using these colors as well as other spectral measures, we determine new criteria for the existence of ongoing and recent starbursts in galaxies.

  7. Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

    Science.gov (United States)

    Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

    2018-06-01

    Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  8. A spectroscopic study of chemical abundances in the globular cluster Omega Centauri

    International Nuclear Information System (INIS)

    Caldwell, S.P.

    1987-10-01

    Blue spectra at a resolution of 0.5 A of red giants in the globular clusters Omega Centauri and NGCs 288, 362, 6397 and 6809 (M55) have been obtained with the Anglo-Australian Telescope. The observations were made to test Sweigart and Mengel's [Astrophy S. J. 229, 624] theory of mixing of nuclearly-processed material to the star's surface, and to elucidate the relationship between primordial and evolutionary origins for the range in abundance within Omega Cen. The Omega Cen stars were chosen in two groups either side of the giant branch, covering the luminosity range where the onset of mixing was predicted to occur. Abundances of C, N, Fe and other heavy elements have been determined by fitting synthetic spectra, calculated from model atmospheres, to the observational data. (author)

  9. THE PECULIAR CHEMICAL INVENTORY OF NGC 2419: AN EXTREME OUTER HALO 'GLOBULAR CLUSTER'

    International Nuclear Information System (INIS)

    Cohen, Judith G.; Kirby, Evan N.; Huang Wenjin

    2011-01-01

    NGC 2419 is a massive outer halo Galactic globular cluster (GC) whose stars have previously been shown to have somewhat peculiar abundance patterns. We have observed seven luminous giants that are members of NGC 2419 with Keck/HIRES at reasonable signal-to-noise ratio. One of these giants is very peculiar, with an extremely low [Mg/Fe] and high [K/Fe] but normal abundances of most other elements. The abundance pattern does not match the nucleosynthetic yields of any supernova model. The other six stars show abundance ratios typical of inner halo Galactic GCs, represented here by a sample of giants in the nearby GC M30. Although our measurements show that NGC 2419 is unusual in some respects, its bulk properties do not provide compelling evidence for a difference between inner and outer halo GCs.

  10. CHEMICAL ABUNDANCES IN NGC 5024 (M53): A MOSTLY FIRST GENERATION GLOBULAR CLUSTER

    International Nuclear Information System (INIS)

    Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico

    2016-01-01

    We present the Fe, Ca, Ti, Ni, Ba, Na, and O abundances for a sample of 53 red giant branch stars in the globular cluster (GC) NGC 5024 (M53). The abundances were measured from high signal-to-noise medium resolution spectra collected with the Hydra multi-object spectrograph on the Wisconsin–Indiana–Yale–NOAO 3.5 m telescope. M53 is of interest because previous studies based on the morphology of the cluster’s horizontal branch suggested that it might be composed primarily of first generation (FG) stars and differ from the majority of other GCs with multiple populations, which have been found to be dominated by the second generation (SG) stars. Our sample has an average [Fe/H] = −2.07 with a standard deviation of 0.07 dex. This value is consistent with previously published results. The alpha-element abundances in our sample are also consistent with the trends seen in Milky Way halo stars at similar metallicities, with enhanced [Ca/Fe] and [Ti/Fe] relative to solar. We find that the Na–O anti-correlation in M53 is not as extended as other GCs with similar masses and metallicities. The ratio of SG to the total number of stars in our sample is approximately 0.27 and the SG generation is more centrally concentrated. These findings further support that M53 might be a mostly FG cluster and could give further insight into how GCs formed the light element abundance patterns we observe in them today.

  11. Chemical Abundances in NGC 5024 (M53): A Mostly First Generation Globular Cluster

    Science.gov (United States)

    Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico

    2016-06-01

    We present the Fe, Ca, Ti, Ni, Ba, Na, and O abundances for a sample of 53 red giant branch stars in the globular cluster (GC) NGC 5024 (M53). The abundances were measured from high signal-to-noise medium resolution spectra collected with the Hydra multi-object spectrograph on the Wisconsin-Indiana-Yale-NOAO 3.5 m telescope. M53 is of interest because previous studies based on the morphology of the cluster’s horizontal branch suggested that it might be composed primarily of first generation (FG) stars and differ from the majority of other GCs with multiple populations, which have been found to be dominated by the second generation (SG) stars. Our sample has an average [Fe/H] = -2.07 with a standard deviation of 0.07 dex. This value is consistent with previously published results. The alpha-element abundances in our sample are also consistent with the trends seen in Milky Way halo stars at similar metallicities, with enhanced [Ca/Fe] and [Ti/Fe] relative to solar. We find that the Na-O anti-correlation in M53 is not as extended as other GCs with similar masses and metallicities. The ratio of SG to the total number of stars in our sample is approximately 0.27 and the SG generation is more centrally concentrated. These findings further support that M53 might be a mostly FG cluster and could give further insight into how GCs formed the light element abundance patterns we observe in them today.

  12. CHEMICAL ABUNDANCES IN NGC 5024 (M53): A MOSTLY FIRST GENERATION GLOBULAR CLUSTER

    Energy Technology Data Exchange (ETDEWEB)

    Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico [Astronomy Department, Indiana University, Bloomington, IN 47405 (United States)

    2016-06-10

    We present the Fe, Ca, Ti, Ni, Ba, Na, and O abundances for a sample of 53 red giant branch stars in the globular cluster (GC) NGC 5024 (M53). The abundances were measured from high signal-to-noise medium resolution spectra collected with the Hydra multi-object spectrograph on the Wisconsin–Indiana–Yale–NOAO 3.5 m telescope. M53 is of interest because previous studies based on the morphology of the cluster’s horizontal branch suggested that it might be composed primarily of first generation (FG) stars and differ from the majority of other GCs with multiple populations, which have been found to be dominated by the second generation (SG) stars. Our sample has an average [Fe/H] = −2.07 with a standard deviation of 0.07 dex. This value is consistent with previously published results. The alpha-element abundances in our sample are also consistent with the trends seen in Milky Way halo stars at similar metallicities, with enhanced [Ca/Fe] and [Ti/Fe] relative to solar. We find that the Na–O anti-correlation in M53 is not as extended as other GCs with similar masses and metallicities. The ratio of SG to the total number of stars in our sample is approximately 0.27 and the SG generation is more centrally concentrated. These findings further support that M53 might be a mostly FG cluster and could give further insight into how GCs formed the light element abundance patterns we observe in them today.

  13. Thermodynamics of non-ideal QGP using Mayers cluster expansion method

    International Nuclear Information System (INIS)

    Prasanth, J.P; Simji, P.; Bannur, Vishnu M.

    2013-01-01

    The Quark gluon plasma (QGP) is the state in which the individual hadrons dissolve into a system of free (or almost free) quarks and gluons in strongly compressed system at high temperature. The present paper aims to calculate the critical temperature at which a non-ideal three quark plasma condenses into droplet of three quarks (i.e., into a liquid of baryons) using Mayers cluster expansion method

  14. GLOBAL CLASSIFICATION OF DERMATITIS DISEASE WITH K-MEANS CLUSTERING IMAGE SEGMENTATION METHODS

    OpenAIRE

    Prafulla N. Aerkewar1 & Dr. G. H. Agrawal2

    2018-01-01

    The objective of this paper to presents a global technique for classification of different dermatitis disease lesions using the process of k-Means clustering image segmentation method. The word global is used such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be analyze and study the segmentation properties of skin lesions occurs in...

  15. A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting

    International Nuclear Information System (INIS)

    Azimi, R.; Ghayekhloo, M.; Ghofrani, M.

    2016-01-01

    Highlights: • A novel clustering approach is proposed based on the data transformation approach. • A novel cluster selection method based on correlation analysis is presented. • The proposed hybrid clustering approach leads to deep learning for MLPNN. • A hybrid forecasting method is developed to predict solar radiations. • The evaluation results show superior performance of the proposed forecasting model. - Abstract: Accurate forecasting of renewable energy sources plays a key role in their integration into the grid. This paper proposes a hybrid solar irradiance forecasting framework using a Transformation based K-means algorithm, named TB K-means, to increase the forecast accuracy. The proposed clustering method is a combination of a new initialization technique, K-means algorithm and a new gradual data transformation approach. Unlike the other K-means based clustering methods which are not capable of providing a fixed and definitive answer due to the selection of different cluster centroids for each run, the proposed clustering provides constant results for different runs of the algorithm. The proposed clustering is combined with a time-series analysis, a novel cluster selection algorithm and a multilayer perceptron neural network (MLPNN) to develop the hybrid solar radiation forecasting method for different time horizons (1 h ahead, 2 h ahead, …, 48 h ahead). The performance of the proposed TB K-means clustering is evaluated using several different datasets and compared with different variants of K-means algorithm. Solar datasets with different solar radiation characteristics are also used to determine the accuracy and processing speed of the developed forecasting method with the proposed TB K-means and other clustering techniques. The results of direct comparison with other well-established forecasting models demonstrate the superior performance of the proposed hybrid forecasting method. Furthermore, a comparative analysis with the benchmark solar

  16. Dynamic Fuzzy Clustering Method for Decision Support in Electricity Markets Negotiation

    Directory of Open Access Journals (Sweden)

    Ricardo FAIA

    2016-10-01

    Full Text Available Artificial Intelligence (AI methods contribute to the construction of systems where there is a need to automate the tasks. They are typically used for problems that have a large response time, or when a mathematical method cannot be used to solve the problem. However, the application of AI brings an added complexity to the development of such applications. AI has been frequently applied in the power systems field, namely in Electricity Markets (EM. In this area, AI applications are essentially used to forecast / estimate the prices of electricity or to search for the best opportunity to sell the product. This paper proposes a clustering methodology that is combined with fuzzy logic in order to perform the estimation of EM prices. The proposed method is based on the application of a clustering methodology that groups historic energy contracts according to their prices’ similarity. The optimal number of groups is automatically calculated taking into account the preference for the balance between the estimation error and the number of groups. The centroids of each cluster are used to define a dynamic fuzzy variable that approximates the tendency of contracts’ history. The resulting fuzzy variable allows estimating expected prices for contracts instantaneously and approximating missing values in the historic contracts.

  17. Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

    Directory of Open Access Journals (Sweden)

    Reilly John J

    2005-06-01

    Full Text Available Abstract Background Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical

  18. Method of waste stabilization with dewatered chemically bonded phosphate ceramics

    Science.gov (United States)

    Wagh, Arun; Maloney, Martin D.

    2010-06-29

    A method of stabilizing a waste in a chemically bonded phosphate ceramic (CBPC). The method consists of preparing a slurry including the waste, water, an oxide binder, and a phosphate binder. The slurry is then allowed to cure to a solid, hydrated CBPC matrix. Next, bound water within the solid, hydrated CBPC matrix is removed. Typically, the bound water is removed by applying heat to the cured CBPC matrix. Preferably, the quantity of heat applied to the cured CBPC matrix is sufficient to drive off water bound within the hydrated CBPC matrix, but not to volatalize other non-water components of the matrix, such as metals and radioactive components. Typically, a temperature range of between 100.degree. C.-200.degree. C. will be sufficient. In another embodiment of the invention wherein the waste and water have been mixed prior to the preparation of the slurry, a select amount of water may be evaporated from the waste and water mixture prior to preparation of the slurry. Another aspect of the invention is a direct anyhydrous CBPC fabrication method wherein water is removed from the slurry by heating and mixing the slurry while allowing the slurry to cure. Additional aspects of the invention are ceramic matrix waste forms prepared by the methods disclosed above.

  19. Usage of K-cluster and factor analysis for grouping and evaluation the quality of olive oil in accordance with physico-chemical parameters

    Science.gov (United States)

    Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Dobreva, M.

    2015-11-01

    25 olive oils were studied- different in origin and ways of extraction, in accordance with 17 physico-chemical parameters as follows: color parameters - a and b, light, fluorescence peaks, pigments - chlorophyll and β-carotene, fatty-acid content. The goals of the current study were: Conducting correlation analysis to find the inner relation between the studied indices; By applying factor analysis with the help of the method of Principal Components (PCA), to reduce the great number of variables into a few factors, which are of main importance for distinguishing the different types of olive oil;Using K-means cluster to compare and group the tested types olive oils based on their similarity. The inner relation between the studied indices was found by applying correlation analysis. A factor analysis using PCA was applied on the basis of the found correlation matrix. Thus the number of the studied indices was reduced to 4 factors, which explained 79.3% from the entire variation. The first one unified the color parameters, β-carotene and the related with oxidative products fluorescence peak - about 520 nm. The second one was determined mainly by the chlorophyll content and related to it fluorescence peak - about 670 nm. The third and the fourth factors were determined by the fatty-acid content of the samples. The third one unified the fatty-acids, which give us the opportunity to distinguish olive oil from the other plant oils - oleic, linoleic and stearin acids. The fourth factor included fatty-acids with relatively much lower content in the studied samples. It is enquired the number of clusters to be determined preliminary in order to apply the K-Cluster analysis. The variant K = 3 was worked out because the types of the olive oil were three. The first cluster unified all salad and pomace olive oils, the second unified the samples of extra virgin oilstaken as controls from producers, which were bought from the trade network. The third cluster unified samples from

  20. Quantum chemical analysis of thermodynamics of 2D cluster formation of alkanes at the water/vapor interface in the presence of aliphatic alcohols.

    Science.gov (United States)

    Vysotsky, Yu B; Kartashynska, E S; Belyaeva, E A; Fainerman, V B; Vollhardt, D; Miller, R

    2015-11-21

    Using the quantum chemical semi-empirical PM3 method it is shown that aliphatic alcohols favor the spontaneous clusterization of vaporous alkanes at the water surface due to the change of adsorption from the barrier to non-barrier mechanism. A theoretical model of the non-barrier mechanism for monolayer formation is developed. In the framework of this model alcohols (or any other surfactants) act as 'floats', which interact with alkane molecules of the vapor phase using their hydrophobic part, whereas the hydrophilic part is immersed into the water phase. This results in a significant increase of contact effectiveness of alkanes with the interface during the adsorption and film formation. The obtained results are in good agreement with the existing experimental data. To test the model the thermodynamic and structural parameters of formation and clusterization are calculated for vaporous alkanes C(n)H(2n+2) (n(CH3) = 6-16) at the water surface in the presence of aliphatic alcohols C(n)H(2n+1)OH (n(OH) = 8-16) at 298 K. It is shown that the values of clusterization enthalpy, entropy and Gibbs' energy per one monomer of the cluster depend on the chain lengths of corresponding alcohols and alkanes, the alcohol molar fraction in the monolayers formed, and the shift of the alkane molecules with respect to the alcohol molecules Δn. Two possible competitive structures of mixed 2D film alkane-alcohol are considered: 2D films 1 with single alcohol molecules enclosed by alkane molecules (the alcohols do not form domains) and 2D films 2 that contain alcohol domains enclosed by alkane molecules. The formation of the alkane films of the first type is nearly independent of the surfactant type present at the interface, but depends on their molar fraction in the monolayer formed and the chain length of the compounds participating in the clusterization, whereas for the formation of the films of the second type the interaction between the hydrophilic parts of the surfactant is

  1. A study of several CAD methods for classification of clustered microcalcifications

    Science.gov (United States)

    Wei, Liyang; Yang, Yongyi; Nishikawa, Robert M.; Jiang, Yulei

    2005-04-01

    In this paper we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs), aimed to assisting radiologists for more accurate diagnosis of breast cancer in a computer-aided diagnosis (CADx) scheme. The methods we consider include: support vector machine (SVM), kernel Fisher discriminant (KFD), and committee machines (ensemble averaging and AdaBoost), most of which have been developed recently in statistical learning theory. We formulate differentiation of malignant from benign MCs as a supervised learning problem, and apply these learning methods to develop the classification algorithms. As input, these methods use image features automatically extracted from clustered MCs. We test these methods using a database of 697 clinical mammograms from 386 cases, which include a wide spectrum of difficult-to-classify cases. We use receiver operating characteristic (ROC) analysis to evaluate and compare the classification performance by the different methods. In addition, we also investigate how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD) yield the best performance, significantly outperforming a well-established CADx approach based on neural network learning.

  2. Environmental data processing by clustering methods for energy forecast and planning

    Energy Technology Data Exchange (ETDEWEB)

    Di Piazza, Annalisa [Dipartimento di Ingegneria Idraulica e Applicazioni Ambientali (DIIAA), viale delle Scienze, Universita degli Studi di Palermo, 90128 Palermo (Italy); Di Piazza, Maria Carmela; Ragusa, Antonella; Vitale, Gianpaolo [Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l' Automazione (ISSIA - CNR), sezione di Palermo, Via Dante, 12, 90141 Palermo (Italy)

    2011-03-15

    This paper presents a statistical approach based on the k-means clustering technique to manage environmental sampled data to evaluate and to forecast of the energy deliverable by different renewable sources in a given site. In particular, wind speed and solar irradiance sampled data are studied in association to the energy capability of a wind generator and a photovoltaic (PV) plant, respectively. The proposed method allows the sub-sets of useful data, describing the energy capability of a site, to be extracted from a set of experimental observations belonging the considered site. The data collection is performed in Sicily, in the south of Italy, as case study. As far as the wind generation is concerned, a suitable generator, matching the wind profile of the studied sites, has been selected for the evaluation of the producible energy. With respect to the photovoltaic generation, the irradiance data have been taken from the acquisition system of an actual installation. It is demonstrated, in both cases, that the use of the k-means clustering method allows data that do not contribute to the produced energy to be grouped into a cluster, moreover it simplifies the problem of the energy assessment since it permits to obtain the desired information on energy capability by managing a reduced amount of experimental samples. In the studied cases, the proposed method permitted a reduction of the 50% of the data with a maximum discrepancy of 10% in energy estimation compared to the classical statistical approach. Therefore, the adopted k-means clustering technique represents an useful tool for an appropriate and less demanding energy forecast and planning in distributed generation systems. (author)

  3. Quantum confinement of lead titanate nanocrystals by wet chemical method

    Energy Technology Data Exchange (ETDEWEB)

    Kaviyarasu, K., E-mail: kaviyarasuloyolacollege@gmail.com [UNESCO-UNISA Africa Chair in Nanosciences/Nanotechnology Laboratories, College of Graduate Studies, University of South Africa (UNISA), Muckleneuk Ridge, P O Box 392, Pretoria (South Africa); Nanosciences African Network (NANOAFNET), Materials Research Department (MSD), iThemba LABS-National Research Foundation - NRF, 1 Old Faure Road, 7129, P O Box 722, Somerset West, Western Cape Province (South Africa); Manikandan, E., E-mail: maniphysics@gmail.com [Nanosciences African Network (NANOAFNET), Materials Research Department (MSD), iThemba LABS-National Research Foundation - NRF, 1 Old Faure Road, 7129, P O Box 722, Somerset West, Western Cape Province (South Africa); Central Research Laboratory, Sree Balaji Medical College & Hospital, Bharath University, Chrompet, Chennai, Tamil Nadu (India); Nuru, Z.Y. [UNESCO-UNISA Africa Chair in Nanosciences/Nanotechnology Laboratories, College of Graduate Studies, University of South Africa (UNISA), Muckleneuk Ridge, P O Box 392, Pretoria (South Africa); Nanosciences African Network (NANOAFNET), Materials Research Department (MSD), iThemba LABS-National Research Foundation - NRF, 1 Old Faure Road, 7129, P O Box 722, Somerset West, Western Cape Province (South Africa); Maaza, M., E-mail: likmaaz@gmail.com [UNESCO-UNISA Africa Chair in Nanosciences/Nanotechnology Laboratories, College of Graduate Studies, University of South Africa (UNISA), Muckleneuk Ridge, P O Box 392, Pretoria (South Africa); Nanosciences African Network (NANOAFNET), Materials Research Department (MSD), iThemba LABS-National Research Foundation - NRF, 1 Old Faure Road, 7129, P O Box 722, Somerset West, Western Cape Province (South Africa)

    2015-11-15

    Lead Titanate (PbTiO{sub 3)} is a category of the practical semiconductor metal oxides, which is widely applied in various scientific and industrial fields because of its catalytic, optical, and electrical properties. PbTiO{sub 3} nanocrystalline materials have attracted a wide attention due to their unique properties. PbTiO{sub 3} nanocrystals were investigated by X-ray diffraction (XRD) to identify the PbTiO{sub 3} nanocrystals were composed a tetragonal structure. The diameter of a single sphere was around 20 nm and the diameter reached up to 3 μm. The chemical composition of the samples and the valence states of elements were determined by X-ray photoelectron spectroscopy (XPS) in detail. - Highlights: • Single crystalline NSs of PbTiO{sub 3} fabricated by wet chemical method. • PbTiO{sub 3} NSs were uniform and continuous along the long axis. • Tetragonal perovskite structure with the diameter 20 nm and length 3 μm. • XPS spectrum was fitted with Lorentzian function respectively. • The size of the images is also 10 μm × 10 μm.

  4. Development of a benchtop baking method for chemically leavened crackers. II. Validation of the method

    Science.gov (United States)

    A benchtop baking method has been developed to predict the contribution of gluten functionality to overall flour performance for chemically leavened crackers. Using a diagnostic formula and procedure, dough rheology was analyzed to evaluate the extent of gluten development during mixing and machinin...

  5. The Peculiar Chemical Inventory of NGC 2419: An Extreme Outer Halo "Globular Cluster"

    Science.gov (United States)

    Cohen, Judith G.; Huang, Wenjin; Kirby, Evan N.

    2011-10-01

    NGC 2419 is a massive outer halo Galactic globular cluster (GC) whose stars have previously been shown to have somewhat peculiar abundance patterns. We have observed seven luminous giants that are members of NGC 2419 with Keck/HIRES at reasonable signal-to-noise ratio. One of these giants is very peculiar, with an extremely low [Mg/Fe] and high [K/Fe] but normal abundances of most other elements. The abundance pattern does not match the nucleosynthetic yields of any supernova model. The other six stars show abundance ratios typical of inner halo Galactic GCs, represented here by a sample of giants in the nearby GC M30. Although our measurements show that NGC 2419 is unusual in some respects, its bulk properties do not provide compelling evidence for a difference between inner and outer halo GCs. Based in part on observations obtained at the W. M. Keck Observatory, which is operated jointly by the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration.

  6. ZnSe thin films by chemical bath deposition method

    Energy Technology Data Exchange (ETDEWEB)

    Lokhande, C.D.; Patil, P.S.; Tributsch, H. [Hahn-Meitner-Institute, Bereich Physikalische Chemie, Abt. CS, Glienicker Strasse-100, D-14109 Berlin (Germany); Ennaoui, A. [Hahn-Meitner-Institute, Bereich Physikalische Chemie, Abt. CG, Glienicker Strasse-100, D-14109 Berlin (Germany)

    1998-09-04

    The ZnSe thin films have been deposited onto glass substrates by the simple chemical bath deposition method using selenourea as a selenide ion source from an aqueous alkaline medium. The effect of Zn ion concentration, bath temperature and deposition time period on the quality and thickness of ZnSe films has been studied. The ZnSe films have been characterized by XRD, TEM, EDAX, TRMC (time-resolved microwave conductivity), optical absorbance and RBS techniques for their structural, compositional, electronic and optical properties. The as-deposited ZnSe films are found to be amorphous, Zn rich with optical band gap, Eg, equal to 2.9 eV

  7. Trace impurities in coal by wet chemical methods

    International Nuclear Information System (INIS)

    Pollock, E.N.

    1975-01-01

    In determining trace elements in coal by wet chemical methods, conventional atomic absorption spectroscopy (AAS) was used to determine Li, Be, V, Cr, Mn, Co, Ni, Cu, Zn, Ag, Cd, and Pb after dry ashing and acid dissolutions. A graphite furnace accessory was used for the flameless AAS determination of Bi, Se, Sn, Te, Be, Pb, As, Cd, Cr, Sb, and Ge. Mercury can be determined by flameless AAS after oxygen bomb combustion. Arsenic and antimony can be determined as their hydrides by AAS after low temperature ashing. Germanium, tin, bismuth, and tellurium can be determined as their hydrides by AAS after high temperature ashing. Selenium can be determined as its hydride by AAS after a special combustion procedure or after oxygen bomb combustion. Fluorine can be determined by specific ion analysis after oxygen bomb combustion. Boron can be determined colorimetrically. (U.S.)

  8. Studies of coupled chemical and catalytic coal conversion methods

    Energy Technology Data Exchange (ETDEWEB)

    Stock, L.M.

    1990-01-01

    This report concerns our research on base-catalyzed coal solubilization and a new approach for hydrogen addition. The work on base-catalyzed, chemical solubilization is continuing. this report is focused on the hydrogenation research. Specifically it deals with the use of arene chromium carbonyl complexes as reagents for the addition of dideuterium to coal molecules. In one phase of the work, he has established that the aromatic hydrocarbons in a representative coal liquid can be converted in very good yield to arene chromium carbonyl compounds. In a second phase of the work directly related to our objective of improved methods for catalytic hydrogenation, he has established that the aromatic constituents of the same coal liquid add dideuterium in the presence of added napththalene chromium carbonyl.

  9. Parity among interpretation methods of MLEE patterns and disparity among clustering methods in epidemiological typing of Candida albicans.

    Science.gov (United States)

    Boriollo, Marcelo Fabiano Gomes; Rosa, Edvaldo Antonio Ribeiro; Gonçalves, Reginaldo Bruno; Höfling, José Francisco

    2006-03-01

    The typing of C. albicans by MLEE (multilocus enzyme electrophoresis) is dependent on the interpretation of enzyme electrophoretic patterns, and the study of the epidemiological relationships of these yeasts can be conducted by cluster analysis. Therefore, the aims of the present study were to first determine the discriminatory power of genetic interpretation (deduction of the allelic composition of diploid organisms) and numerical interpretation (mere determination of the presence and absence of bands) of MLEE patterns, and then to determine the concordance (Pearson product-moment correlation coefficient) and similarity (Jaccard similarity coefficient) of the groups of strains generated by three cluster analysis models, and the discriminatory power of such models as well [model A: genetic interpretation, genetic distance matrix of Nei (d(ij)) and UPGMA dendrogram; model B: genetic interpretation, Dice similarity matrix (S(D1)) and UPGMA dendrogram; model C: numerical interpretation, Dice similarity matrix (S(D2)) and UPGMA dendrogram]. MLEE was found to be a powerful and reliable tool for the typing of C. albicans due to its high discriminatory power (>0.9). Discriminatory power indicated that numerical interpretation is a method capable of discriminating a greater number of strains (47 versus 43 subtypes), but also pointed to model B as a method capable of providing a greater number of groups, suggesting its use for the typing of C. albicans by MLEE and cluster analysis. Very good agreement was only observed between the elements of the matrices S(D1) and S(D2), but a large majority of the groups generated in the three UPGMA dendrograms showed similarity S(J) between 4.8% and 75%, suggesting disparities in the conclusions obtained by the cluster assays.

  10. A quasiparticle-based multi-reference coupled-cluster method.

    Science.gov (United States)

    Rolik, Zoltán; Kállay, Mihály

    2014-10-07

    The purpose of this paper is to introduce a quasiparticle-based multi-reference coupled-cluster (MRCC) approach. The quasiparticles are introduced via a unitary transformation which allows us to represent a complete active space reference function and other elements of an orthonormal multi-reference (MR) basis in a determinant-like form. The quasiparticle creation and annihilation operators satisfy the fermion anti-commutation relations. On the basis of these quasiparticles, a generalization of the normal-ordered operator products for the MR case can be introduced as an alternative to the approach of Mukherjee and Kutzelnigg [Recent Prog. Many-Body Theor. 4, 127 (1995); Mukherjee and Kutzelnigg, J. Chem. Phys. 107, 432 (1997)]. Based on the new normal ordering any quasiparticle-based theory can be formulated using the well-known diagram techniques. Beyond the general quasiparticle framework we also present a possible realization of the unitary transformation. The suggested transformation has an exponential form where the parameters, holding exclusively active indices, are defined in a form similar to the wave operator of the unitary coupled-cluster approach. The definition of our quasiparticle-based MRCC approach strictly follows the form of the single-reference coupled-cluster method and retains several of its beneficial properties. Test results for small systems are presented using a pilot implementation of the new approach and compared to those obtained by other MR methods.

  11. Clustering method for counting passengers getting in a bus with single camera

    Science.gov (United States)

    Yang, Tao; Zhang, Yanning; Shao, Dapei; Li, Ying

    2010-03-01

    Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.

  12. A New Cluster Analysis-Marker-Controlled Watershed Method for Separating Particles of Granular Soils.

    Science.gov (United States)

    Alam, Md Ferdous; Haque, Asadul

    2017-10-18

    An accurate determination of particle-level fabric of granular soils from tomography data requires a maximum correct separation of particles. The popular marker-controlled watershed separation method is widely used to separate particles. However, the watershed method alone is not capable of producing the maximum separation of particles when subjected to boundary stresses leading to crushing of particles. In this paper, a new separation method, named as Monash Particle Separation Method (MPSM), has been introduced. The new method automatically determines the optimal contrast coefficient based on cluster evaluation framework to produce the maximum accurate separation outcomes. Finally, the particles which could not be separated by the optimal contrast coefficient were separated by integrating cuboid markers generated from the clustering by Gaussian mixture models into the routine watershed method. The MPSM was validated on a uniformly graded sand volume subjected to one-dimensional compression loading up to 32 MPa. It was demonstrated that the MPSM is capable of producing the best possible separation of particles required for the fabric analysis.

  13. application of single-linkage clustering method in the analysis of ...

    African Journals Online (AJOL)

    Admin

    ANALYSIS OF GROWTH RATE OF GROSS DOMESTIC PRODUCT. (GDP) AT ... The end result of the algorithm is a tree of clusters called a dendrogram, which shows how the clusters are ..... Number of cluster sum from from observations of ...

  14. Aggregation-induced chemical reactions: acid dissociation in growing water clusters.

    Science.gov (United States)

    Forbert, Harald; Masia, Marco; Kaczmarek-Kedziera, Anna; Nair, Nisanth N; Marx, Dominik

    2011-03-23

    Understanding chemical reactivity at ultracold conditions, thus enabling molecular syntheses via interstellar and atmospheric processes, is a key issue in cryochemistry. In particular, acid dissociation and proton transfer reactions are ubiquitous in aqueous microsolvation environments. Here, the full dissociation of a HCl molecule upon stepwise solvation by a small number of water molecules at low temperatures, as relevant to helium nanodroplet isolation (HENDI) spectroscopy, is analyzed in mechanistic detail. It is found that upon successive aggregation of HCl with H(2)O molecules, a series of cyclic heteromolecular structures, up to and including HCl(H(2)O)(3), are initially obtained before a precursor state for dissociation, HCl(H(2)O)(3)···H(2)O, is observed upon addition of a fourth water molecule. The latter partially aggregated structure can be viewed as an "activated species", which readily leads to dissociation of HCl and to the formation of a solvent-shared ion pair, H(3)O(+)(H(2)O)(3)Cl(-). Overall, the process is mostly downhill in potential energy, and, in addition, small remaining barriers are overcome by using kinetic energy released as a result of forming hydrogen bonds due to aggregation. The associated barrier is not ruled by thermal equilibrium but is generated by athermal non-equilibrium dynamics. These "aggregation-induced chemical reactions" are expected to be of broad relevance to chemistry at ultralow temperature much beyond HENDI spectroscopy.

  15. A novel intrusion detection method based on OCSVM and K-means recursive clustering

    Directory of Open Access Journals (Sweden)

    Leandros A. Maglaras

    2015-01-01

    Full Text Available In this paper we present an intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system, based on the combination of One-Class Support Vector Machine (OCSVM with RBF kernel and recursive k-means clustering. Important parameters of OCSVM, such as Gaussian width o and parameter v affect the performance of the classifier. Tuning of these parameters is of great importance in order to avoid false positives and over fitting. The combination of OCSVM with recursive k- means clustering leads the proposed intrusion detection module to distinguish real alarms from possible attacks regardless of the values of parameters o and v, making it ideal for real-time intrusion detection mechanisms for SCADA systems. Extensive simulations have been conducted with datasets extracted from small and medium sized HTB SCADA testbeds, in order to compare the accuracy, false alarm rate and execution time against the base line OCSVM method.

  16. New Target for an Old Method: Hubble Measures Globular Cluster Parallax

    Science.gov (United States)

    Hensley, Kerry

    2018-05-01

    Measuring precise distances to faraway objects has long been a challenge in astrophysics. Now, one of the earliest techniques used to measure the distance to astrophysical objects has been applied to a metal-poor globular cluster for the first time.A Classic TechniqueAn artists impression of the European Space Agencys Gaia spacecraft. Gaia is on track to map the positions and motions of a billion stars. [ESA]Distances to nearby stars are often measured using the parallax technique tracing the tiny apparent motion of a target star against the background of more distant stars as Earth orbits the Sun. This technique has come a long way since it was first used in the 1800s to measure the distance to stars a few tens of light-years away; with the advent of space observatories like Hipparcos and Gaia, parallax can now be used to map the positions of stars out to thousands of light-years.Precise distance measurements arent only important for setting the scale of the universe, however; they can also help us better understand stellar evolution over the course of cosmic history. Stellar evolution models are often anchored to a reference star cluster, the properties of which must be known precisely. These precise properties can be readily determined for young, nearby open clusters using parallax measurements. But stellar evolution models that anchor on themore-distant, ancient, metal-poor globular clusters have been hampered by theless-precise indirect methods used tomeasure distance to these faraway clusters until now.Top: An image of NGC 6397 overlaid with the area scanned by Hubble (dashed green) and the footprint of the camera (solid green). The blue ellipse represents the parallax motion of a star in the cluster, exaggerated by a factor of ten thousand. Bottom: An example scan from this field. [Adapted from Brown et al. 2018]New Measurement to an Old ClusterThomas Brown (Space Telescope Science Institute) and collaborators used the Hubble Space Telescope todetermine the

  17. Consumers' Kansei Needs Clustering Method for Product Emotional Design Based on Numerical Design Structure Matrix and Genetic Algorithms.

    Science.gov (United States)

    Yang, Yan-Pu; Chen, Deng-Kai; Gu, Rong; Gu, Yu-Feng; Yu, Sui-Huai

    2016-01-01

    Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.

  18. Impact of physical and chemical parameters on the hydroxyapatite nanopowder synthesized by chemical precipitation method

    Science.gov (United States)

    Thu Trang Pham, Thi; Phuong Nguyen, Thu; Pham, Thi Nam; Phuong Vu, Thi; Tran, Dai Lam; Thai, Hoang; Thanh Dinh, Thi Mai

    2013-09-01

    In this paper, the synthesis of hydroxyapatite (HAp) nanopowder was studied by chemical precipitation method at different values of reaction temperature, settling time, Ca/P ratio, calcination temperature, (NH4)2HPO4 addition rate, initial concentration of Ca(NO3)2 and (NH4)2HPO4. Analysis results of properties, morphology, structure of HAp powder from infrared (IR) spectra, x-ray diffraction (XRD), energy dispersive x-ray (EDX) spectra and scanning electron microscopy (SEM) indicated that the synthesized HAp powder had cylinder crystal shape with size less than 100 nm, single-phase structure. The variation of the synthesis conditions did not affect the morphology but affected the size of HAp crystals.

  19. Hydration structure and dynamics of a hydroxide ion in water clusters of varying size and temperature: Quantum chemical and ab initio molecular dynamics studies

    International Nuclear Information System (INIS)

    Bankura, Arindam; Chandra, Amalendu

    2012-01-01

    Highlights: ► A theoretical study of hydroxide ion-water clusters is carried for varying cluster size and temperature. ► The structures of OH − (H 2 O) n are found out through quantum chemical calculations for n = 4, 8, 16 and 20. ► The finite temperature behavior of the clusters is studied through ab initio dynamical simulations. ► The spectral features of OH modes (deuterated) and their dependence on hydrogen bonding states of water are discussed. ► The mechanism and kinetics of proton transfer processes in these anionic clusters are also investigated. - Abstract: We have investigated the hydration structure and dynamics of OH − (H 2 O) n clusters (n = 4, 8, 16 and 20) by means of quantum chemical and ab initio molecular dynamics calculations. Quantum chemical calculations reveal that the solvation structure of the hydroxide ion transforms from three and four-coordinated surface states to five-coordinated interior state with increase in cluster size. Several other isomeric structures with energies not very different from the most stable isomer are also found. Ab initio simulations show that the most probable configurations at higher temperatures need not be the lowest energy isomeric structure. The rates of proton transfer in these clusters are found to be slower than that in bulk water. The vibrational spectral calculations reveal distinct features for free OH (deuterated) stretch modes of water in different hydrogen bonding states. Effects of temperature on the structural and dynamical properties are also investigated for the largest cluster considered here.

  20. Chimera and phase-cluster states in populations of coupled chemical oscillators

    Science.gov (United States)

    Tinsley, Mark R.; Nkomo, Simbarashe; Showalter, Kenneth

    2012-09-01

    Populations of coupled oscillators may exhibit two coexisting subpopulations, one with synchronized oscillations and the other with unsynchronized oscillations, even though all of the oscillators are coupled to each other in an equivalent manner. This phenomenon, discovered about ten years ago in theoretical studies, was then further characterized and named the chimera state after the Greek mythological creature made up of different animals. The highly counterintuitive coexistence of coherent and incoherent oscillations in populations of identical oscillators, each with an equivalent coupling structure, inspired great interest and a flurry of theoretical activity. Here we report on experimental studies of chimera states and their relation to other synchronization states in populations of coupled chemical oscillators. Our experiments with coupled Belousov-Zhabotinsky oscillators and corresponding simulations reveal chimera behaviour that differs significantly from the behaviour found in theoretical studies of phase-oscillator models.

  1. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

    Directory of Open Access Journals (Sweden)

    Yonghao Gu

    2017-01-01

    Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

  2. New method for reconstruction of star spatial distribution in globular clusters and its application to flare stars in Pleiades

    International Nuclear Information System (INIS)

    Kosarev, E.L.

    1980-01-01

    A new method to reconstruct spatial star distribution in globular clusters is presented. The method gives both the estimation of unknown spatial distribution and the probable reconstruction error. This error has statistical origin and depends only on the number of stars in a cluster. The method is applied to reconstruct the spatial density of 441 flare stars in Pleiades. The spatial density has a maximum in the centre of the cluster of about 1.6-2.5 pc -3 and with increasing distance from the center smoothly falls down to zero approximately with the Gaussian law with a scale parameter of 3.5 pc

  3. K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

    Directory of Open Access Journals (Sweden)

    Lv Tao

    2017-01-01

    Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.

  4. A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.

    Directory of Open Access Journals (Sweden)

    Daniel M de Brito

    Full Text Available Genomic Islands (GIs are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP--Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.

  5. A new method to cluster genomes based on cumulative Fourier power spectrum.

    Science.gov (United States)

    Dong, Rui; Zhu, Ziyue; Yin, Changchuan; He, Rong L; Yau, Stephen S-T

    2018-06-20

    Analyzing phylogenetic relationships using mathematical methods has always been of importance in bioinformatics. Quantitative research may interpret the raw biological data in a precise way. Multiple Sequence Alignment (MSA) is used frequently to analyze biological evolutions, but is very time-consuming. When the scale of data is large, alignment methods cannot finish calculation in reasonable time. Therefore, we present a new method using moments of cumulative Fourier power spectrum in clustering the DNA sequences. Each sequence is translated into a vector in Euclidean space. Distances between the vectors can reflect the relationships between sequences. The mapping between the spectra and moment vector is one-to-one, which means that no information is lost in the power spectra during the calculation. We cluster and classify several datasets including Influenza A, primates, and human rhinovirus (HRV) datasets to build up the phylogenetic trees. Results show that the new proposed cumulative Fourier power spectrum is much faster and more accurately than MSA and another alignment-free method known as k-mer. The research provides us new insights in the study of phylogeny, evolution, and efficient DNA comparison algorithms for large genomes. The computer programs of the cumulative Fourier power spectrum are available at GitHub (https://github.com/YaulabTsinghua/cumulative-Fourier-power-spectrum). Copyright © 2018. Published by Elsevier B.V.

  6. Test Methods for Evaluating Solid Waste, Physical/Chemical Methods. First Update. (3rd edition)

    International Nuclear Information System (INIS)

    Friedman; Sellers.

    1988-01-01

    The proposed Update is for Test Methods for Evaluating Solid Waste, Physical/Chemical Methods, SW-846, Third Edition. Attached to the report is a list of methods included in the proposed update indicating whether the method is a new method, a partially revised method, or a totally revised method. Do not discard or replace any of the current pages in the SW-846 manual until the proposed update I package is promulgated. Until promulgation of the update package, the methods in the update package are not officially part of the SW-846 manual and thus do not carry the status of EPA-approved methods. In addition to the proposed Update, six finalized methods are included for immediate inclusion into the Third Edition of SW-846. Four methods, originally proposed October 1, 1984, will be finalized in a soon to be released rulemaking. They are, however, being submitted to subscribers for the first time in the update. These methods are 7211, 7381, 7461, and 7951. Two other methods were finalized in the 2nd Edition of SW-846. They were inadvertantly omitted from the 3rd Edition and are not being proposed as new. These methods are 7081 and 7761

  7. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  8. Data Clustering on Breast Cancer Data Using Firefly Algorithm with Golden Ratio Method

    Directory of Open Access Journals (Sweden)

    DEMIR, M.

    2015-05-01

    Full Text Available Heuristic methods are problem solving methods. In general, they obtain near-optimal solutions, and they do not take the care of provability of this case. The heuristic methods do not guarantee to obtain the optimal results; however, they guarantee to obtain near-optimal solutions in considerable time. In this paper, an application was performed by using firefly algorithm - one of the heuristic methods. The golden ratio was applied to different steps of firefly algorithm and different parameters of firefly algorithm to develop a new algorithm - called Firefly Algorithm with Golden Ratio (FAGR. It was shown that the golden ratio made firefly algorithm be superior to the firefly algorithm without golden ratio. At this aim, the developed algorithm was applied to WBCD database (breast cancer database to cluster data obtained from breast cancer patients. The highest obtained success rate among all executions is 96% and the highest obtained average success rate in all executions is 94.5%.

  9. An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

    Science.gov (United States)

    Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

    2018-04-01

    Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

  10. Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

    Science.gov (United States)

    Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

    2009-02-01

    Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

  11. Don't spin the pen: two alternative methods for second-stage sampling in urban cluster surveys

    Directory of Open Access Journals (Sweden)

    Rose Angela MC

    2007-06-01

    Full Text Available Abstract In two-stage cluster surveys, the traditional method used in second-stage sampling (in which the first household in a cluster is selected is time-consuming and may result in biased estimates of the indicator of interest. Firstly, a random direction from the center of the cluster is selected, usually by spinning a pen. The houses along that direction are then counted out to the boundary of the cluster, and one is then selected at random to be the first household surveyed. This process favors households towards the center of the cluster, but it could easily be improved. During a recent meningitis vaccination coverage survey in Maradi, Niger, we compared this method of first household selection to two alternatives in urban zones: 1 using a superimposed grid on the map of the cluster area and randomly selecting an intersection; and 2 drawing the perimeter of the cluster area using a Global Positioning System (GPS and randomly selecting one point within the perimeter. Although we only compared a limited number of clusters using each method, we found the sampling grid method to be the fastest and easiest for field survey teams, although it does require a map of the area. Selecting a random GPS point was also found to be a good method, once adequate training can be provided. Spinning the pen and counting households to the boundary was the most complicated and time-consuming. The two methods tested here represent simpler, quicker and potentially more robust alternatives to spinning the pen for cluster surveys in urban areas. However, in rural areas, these alternatives would favor initial household selection from lower density (or even potentially empty areas. Bearing in mind these limitations, as well as available resources and feasibility, investigators should choose the most appropriate method for their particular survey context.

  12. A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

    Science.gov (United States)

    Ferrari, Alberto; Comelli, Mario

    2016-12-01

    In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Analytical Energy Gradients for Excited-State Coupled-Cluster Methods

    Science.gov (United States)

    Wladyslawski, Mark; Nooijen, Marcel

    The equation-of-motion coupled-cluster (EOM-CC) and similarity transformed equation-of-motion coupled-cluster (STEOM-CC) methods have been firmly established as accurate and routinely applicable extensions of single-reference coupled-cluster theory to describe electronically excited states. An overview of these methods is provided, with emphasis on the many-body similarity transform concept that is the key to a rationalization of their accuracy. The main topic of the paper is the derivation of analytical energy gradients for such non-variational electronic structure approaches, with an ultimate focus on obtaining their detailed algebraic working equations. A general theoretical framework using Lagrange's method of undetermined multipliers is presented, and the method is applied to formulate the EOM-CC and STEOM-CC gradients in abstract operator terms, following the previous work in [P.G. Szalay, Int. J. Quantum Chem. 55 (1995) 151] and [S.R. Gwaltney, R.J. Bartlett, M. Nooijen, J. Chem. Phys. 111 (1999) 58]. Moreover, the systematics of the Lagrange multiplier approach is suitable for automation by computer, enabling the derivation of the detailed derivative equations through a standardized and direct procedure. To this end, we have developed the SMART (Symbolic Manipulation and Regrouping of Tensors) package of automated symbolic algebra routines, written in the Mathematica programming language. The SMART toolkit provides the means to expand, differentiate, and simplify equations by manipulation of the detailed algebraic tensor expressions directly. The Lagrangian multiplier formulation establishes a uniform strategy to perform the automated derivation in a standardized manner: A Lagrange multiplier functional is constructed from the explicit algebraic equations that define the energy in the electronic method; the energy functional is then made fully variational with respect to all of its parameters, and the symbolic differentiations directly yield the explicit

  14. Dancoff factors with partial absorption in cluster geometry by the direct method

    International Nuclear Information System (INIS)

    Rodrigues, Leticia Jenisch; Leite, Sergio de Queiroz Bogado; Vilhena, Marco Tullio de; Bodmann, Bardo Ernest Josef

    2007-01-01

    Accurate analysis of resonance absorption in heterogeneous systems is essential in problems like criticality, breeding ratios and fuel depletion calculations. In compact arrays of fuel rods, resonance absorption is strongly affected by the Dancoff factor, defined in this study as the probability that a neutron emitted from the surface of a fuel element, enters another fuel element without any collision in the moderator or cladding. In the original WIMS code, Black Dancoff factors were computed in cluster geometry by the collision probability method, for each one of the symmetrically distinct fuel pin positions in the cell. Recent improvements to the code include a new routine (PIJM) that was created to incorporate a more efficient scheme for computing the collision matrices. In that routine, each system region is considered individually, minimizing convergence problems and reducing the number of neutron track lines required in the in-plane integrations of the Bickley functions for any given accuracy. In the present work, PIJM is extended to compute Grey Dancoff factors for two-dimensional cylindrical cells in cluster geometry. The effectiveness of the method is accessed by comparing Grey Dancoff factors as calculated by PIJM, with those available in the literature by the Monte Carlo method, for the irregular geometry of the Canadian CANDU37 assembly. Dancoff factors at five symmetrically distinct fuel pin positions are found in very good agreement with the literature results (author)

  15. A robust automatic leukocyte recognition method based on island-clustering texture

    Directory of Open Access Journals (Sweden)

    Xiaoshun Li

    2016-01-01

    Full Text Available A leukocyte recognition method for human peripheral blood smear based on island-clustering texture (ICT is proposed. By analyzing the features of the five typical classes of leukocyte images, a new ICT model is established. Firstly, some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands. Secondly, the growing region is employed to create regions of the islands in which the seeds are just these feature points. These islands distribution can describe a new texture. Finally, a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte. Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3% with a total sample of 1310 leukocytes. Experimental results show the feasibility of the proposed method. Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.

  16. How to compute isomerization energies of organic molecules with quantum chemical methods.

    Science.gov (United States)

    Grimme, Stefan; Steinmetz, Marc; Korth, Martin

    2007-03-16

    The reaction energies for 34 typical organic isomerizations including oxygen and nitrogen heteroatoms are investigated with modern quantum chemical methods that have the perspective of also being applicable to large systems. The experimental reaction enthalpies are corrected for vibrational and thermal effects, and the thus derived "experimental" reaction energies are compared to corresponding theoretical data. A series of standard AO basis sets in combination with second-order perturbation theory (MP2, SCS-MP2), conventional density functionals (e.g., PBE, TPSS, B3-LYP, MPW1K, BMK), and new perturbative functionals (B2-PLYP, mPW2-PLYP) are tested. In three cases, obvious errors of the experimental values could be detected, and accurate coupled-cluster [CCSD(T)] reference values have been used instead. It is found that only triple-zeta quality AO basis sets provide results close enough to the basis set limit and that sets like the popular 6-31G(d) should be avoided in accurate work. Augmentation of small basis sets with diffuse functions has a notable effect in B3-LYP calculations that is attributed to intramolecular basis set superposition error and covers basic deficiencies of the functional. The new methods based on perturbation theory (SCS-MP2, X2-PLYP) are found to be clearly superior to many other approaches; that is, they provide mean absolute deviations of less than 1.2 kcal mol-1 and only a few (computational thermochemistry methods.

  17. Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

    Science.gov (United States)

    Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.

    2010-06-01

    of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.

  18. A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yongwei Zhang

    2017-01-01

    Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

  19. Integration of Qualitative and Quantitative Methods: Building and Interpreting Clusters from Grounded Theory and Discourse Analysis

    Directory of Open Access Journals (Sweden)

    Aldo Merlino

    2007-01-01

    Full Text Available Qualitative methods present a wide spectrum of application possibilities as well as opportunities for combining qualitative and quantitative methods. In the social sciences fruitful theoretical discussions and a great deal of empirical research have taken place. This article introduces an empirical investigation which demonstrates the logic of combining methodologies as well as the collection and interpretation, both sequential as simultaneous, of qualitative and quantitative data. Specifically, the investigation process will be described, beginning with a grounded theory methodology and its combination with the techniques of structural semiotics discourse analysis to generate—in a first phase—an instrument for quantitative measuring and to understand—in a second phase—clusters obtained by quantitative analysis. This work illustrates how qualitative methods allow for the comprehension of the discursive and behavioral elements under study, and how they function as support making sense of and giving meaning to quantitative data. URN: urn:nbn:de:0114-fqs0701219

  20. A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB.

    Science.gov (United States)

    Kent, Peter; Jensen, Rikke K; Kongsted, Alice

    2014-10-02

    There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets

  1. Pattern Classification of Tropical Cyclone Tracks over the Western North Pacific using a Fuzzy Clustering Method

    Science.gov (United States)

    Kim, H.; Ho, C.; Kim, J.

    2008-12-01

    This study presents the pattern classification of tropical cyclone (TC) tracks over the western North Pacific (WNP) basin during the typhoon season (June through October) for 1965-2006 (total 42 years) using a fuzzy clustering method. After the fuzzy c-mean clustering algorithm to the TC trajectory interpolated into 20 segments of equivalent length, we divided the whole tracks into 7 patterns. The optimal number of the fuzzy cluster is determined by several validity measures. The classified TC track patterns represent quite different features in the recurving latitudes, genesis locations, and geographical pathways: TCs mainly forming in east-northern part of the WNP and striking Korean and Japan (C1); mainly forming in west-southern part of the WNP, traveling long pathway, and partly striking Japan (C2); mainly striking Taiwan and East China (C3); traveling near the east coast of Japan (C4); traveling the distant ocean east of Japan (C5); moving toward South China and Vietnam straightly (C6); and forming in the South China Sea (C7). Atmospheric environments related to each cluster show physically consistent with each TC track patterns. The straight track pattern is closely linked to a developed anticyclonic circulation to the north of the TC. It implies that this ridge acts as a steering flow forcing TCs to move to the northwest with a more west-oriented track. By contrast, recurving patterns occur commonly under the influence of the strong anomalous westerlies over the TC pathway but there definitely exist characteristic anomalous circulations over the mid- latitudes by pattern. Some clusters are closely related to the well-known large-scale phenomena. The C1 and C2 are highly related to the ENSO phase: The TCs in the C1 (C2) is more active during La Niña (El Niño). The TC activity in the C3 is associated with the WNP summer monsoon. The TCs in the C4 is more (less) vigorous during the easterly (westerly) phase of the stratospheric quasi-biennial oscillation

  2. Statistical method for determining ages of globular clusters by fitting isochrones

    International Nuclear Information System (INIS)

    Flannery, B.P.; Johnson, B.C.

    1982-01-01

    We describe a statistical procedure to compare models of stellar evolution and atmospheres with color-magnitude diagrams of globular clusters. The isochrone depends on five parameters: m-M, age, [Fe/H], Y, and α, but in practice we can only determine m-M and age for an assumed composition. The technique allows us to determine parameters of the model, their uncertainty, and to assess goodness of fit. We test the method, and evaluate the effect of assumptions on an extensive set of Monte Carlo simulations. We apply the method to extensive observations of NGC 6752 and M5, and to smaller data sets for the clusters M3, M5, M15, and M92. We determine age and m-M for two assumed values of helium Y = (0.2, 0.3), and three values of metallicity with a spread in [Fe/H] of +- 0.3 dex. These result in a spread in age of 5-8 Gyr (1 Gyr = 10 9 yr), and a spread in m-M of 0.5 mag. The mean age is generally younger by 2-3 Gyr than previous estimates. Likely uncertainty associated with an individual fit can be small as 0.4 Gyr. Most importantly, we find that two uncalibratable sources of systematic error make the results suspect. These are uncertainty in the stellar temperatures induced by choice of mixing length, and known errors in stellar atmospheres. These effects could reduce age estimates by an additional 5 Gyr. We conclude that observations do not preclude ages as young as 10 Gyr for globular clusters

  3. Physical-chemical property based sequence motifs and methods regarding same

    Science.gov (United States)

    Braun, Werner [Friendswood, TX; Mathura, Venkatarajan S [Sarasota, FL; Schein, Catherine H [Friendswood, TX

    2008-09-09

    A data analysis system, program, and/or method, e.g., a data mining/data exploration method, using physical-chemical property motifs. For example, a sequence database may be searched for identifying segments thereof having physical-chemical properties similar to the physical-chemical property motifs.

  4. Comparison Of Keyword Based Clustering Of Web Documents By Using Openstack 4j And By Traditional Method

    Directory of Open Access Journals (Sweden)

    Shiza Anand

    2015-08-01

    Full Text Available As the number of hypertext documents are increasing continuously day by day on world wide web. Therefore clustering methods will be required to bind documents into the clusters repositories according to the similarity lying between the documents. Various clustering methods exist such as Hierarchical Based K-means Fuzzy Logic Based Centroid Based etc. These keyword based clustering methods takes much more amount of time for creating containers and putting documents in their respective containers. These traditional methods use File Handling techniques of different programming languages for creating repositories and transferring web documents into these containers. In contrast openstack4j SDK is a new technique for creating containers and shifting web documents into these containers according to the similarity in much more less amount of time as compared to the traditional methods. Another benefit of this technique is that this SDK understands and reads all types of files such as jpg html pdf doc etc. This paper compares the time required for clustering of documents by using openstack4j and by traditional methods and suggests various search engines to adopt this technique for clustering so that they give result to the user querries in less amount of time.

  5. Stability of maximum-likelihood-based clustering methods: exploring the backbone of classifications

    International Nuclear Information System (INIS)

    Mungan, Muhittin; Ramasco, José J

    2010-01-01

    Components of complex systems are often classified according to the way they interact with each other. In graph theory such groups are known as clusters or communities. Many different techniques have been recently proposed to detect them, some of which involve inference methods using either Bayesian or maximum likelihood approaches. In this paper, we study a statistical model designed for detecting clusters based on connection similarity. The basic assumption of the model is that the graph was generated by a certain grouping of the nodes and an expectation maximization algorithm is employed to infer that grouping. We show that the method admits further development to yield a stability analysis of the groupings that quantifies the extent to which each node influences its neighbors' group membership. Our approach naturally allows for the identification of the key elements responsible for the grouping and their resilience to changes in the network. Given the generality of the assumptions underlying the statistical model, such nodes are likely to play special roles in the original system. We illustrate this point by analyzing several empirical networks for which further information about the properties of the nodes is available. The search and identification of stabilizing nodes constitutes thus a novel technique to characterize the relevance of nodes in complex networks

  6. A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2012-06-08

    AbstractBackgroundThe localization of proteins to specific subcellular structures in eukaryotic cells provides important information with respect to their function. Fluorescence microscopy approaches to determine localization distribution have proved to be an essential tool in the characterization of unknown proteins, and are now particularly pertinent as a result of the wide availability of fluorescently-tagged constructs and antibodies. However, there are currently very few image analysis options able to effectively discriminate proteins with apparently similar distributions in cells, despite this information being important for protein characterization.FindingsWe have developed a novel method for combining two existing image analysis approaches, which results in highly efficient and accurate discrimination of proteins with seemingly similar distributions. We have combined image texture-based analysis with quantitative co-localization coefficients, a method that has traditionally only been used to study the spatial overlap between two populations of molecules. Here we describe and present a novel application for quantitative co-localization, as applied to the study of Rab family small GTP binding proteins localizing to the endomembrane system of cultured cells.ConclusionsWe show how quantitative co-localization can be used alongside texture feature analysis, resulting in improved clustering of microscopy images. The use of co-localization as an additional clustering parameter is non-biased and highly applicable to high-throughput image data sets.

  7. Measuring Group Synchrony: A Cluster-Phase Method for Analyzing Multivariate Movement Time-Series

    Directory of Open Access Journals (Sweden)

    Michael eRichardson

    2012-10-01

    Full Text Available A new method for assessing group synchrony is introduced as being potentially useful for objectively determining degree of group cohesiveness or entitativity. The cluster-phase method of Frank and Richardson (2010 was used to analyze movement data from the rocking chair movements of six-member groups who rocked their chairs while seated in a circle facing the center. In some trials group members had no information about others’ movements (their eyes were shut or they had their eyes open and gazed at a marker in the center of the group. As predicted, the group level synchrony measure was able to distinguish between situations where synchrony would have been possible and situations where it would be impossible. Moreover, other aspects of the analysis illustrated how the cluster phase measures can be used to determine the type of patterning of group synchrony, and, when integrated with multi-level modeling, can be used to examine individual-level differences in synchrony and dyadic level synchrony as well.

  8. The multi-scattering-Xα method for analysis of the electronic structure of atomic clusters

    International Nuclear Information System (INIS)

    Bahurmuz, A.A.; Woo, C.H.

    1984-12-01

    A computer program, MSXALPHA, has been developed to carry out a quantum-mechanical analysis of the electronic structure of molecules and atomic clusters using the Multi-Scattering-Xα (MSXα) method. The MSXALPHA program is based on a code obtained from the University of Alberta; several improvements and new features were incorporated to increase generality and efficiency. The major ones are: (1) minimization of core memory usage, (2) reduction of execution time, (3) introduction of a dynamic core allocation scheme for a large number of arrays, (4) incorporation of an atomic program to generate numerical orbitals used to construct the initial molecular potential, and (5) inclusion of a routine to evaluate total energy. This report is divided into three parts. The first discusses the theory of the MSXα method. The second gives a detailed description of the program, MSXALPHA. The third discusses the results of calculations carried out for the methane molecule (CH 4 ) and a four-atom zirconium cluster (Zr 4 )

  9. A numerical study of spin-dependent organization of alkali-metal atomic clusters using density-functional method

    International Nuclear Information System (INIS)

    Liu Xuan; Ito, Haruhiko; Torikai, Eiko

    2012-01-01

    We calculate the different geometric isomers of spin clusters composed of a small number of alkali-metal atoms using the UB3LYP density-functional method. The electron density distribution of clusters changes according to the value of total spin. Steric structures as well as planar structures arise when the number of atoms increases. The lowest spin state is the most stable and Li n , Na n , K n , Rb n , and Cs n with n = 2–8 can be formed in higher spin states. In the highest spin state, the preparation of clusters depends on the kind and the number of constituent atoms. The interaction energy between alkali-metal atoms and rare-gas atoms is smaller than the binding energy of spin clusters. Consequently, it is possible to self-organize the alkali-metal-atom clusters on a non-wetting substrate coated with rare-gas atoms.

  10. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L., E-mail: prii.ramos@gmail.com, E-mail: camunita@ipen.br, E-mail: alapolli@ipen.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)

    2017-07-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  11. Validity studies among hierarchical methods of cluster analysis using cophenetic correlation coefficient

    International Nuclear Information System (INIS)

    Carvalho, Priscilla R.; Munita, Casimiro S.; Lapolli, André L.

    2017-01-01

    The literature presents many methods for partitioning of data base, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data base. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data base of the Archaeometric Studies Group from IPEN-CNEN/SP, in which 45 samples of ceramic fragments from three archaeological sites were analyzed by instrumental neutron activation analysis (INAA) which were determinate the mass fraction of 13 elements (As, Ce, Cr, Eu, Fe, Hf, La, Na, Nd, Sc, Sm, Th, U). The methods used for this study were: single linkage, complete linkage, average linkage, centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data base. (author)

  12. A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

    Directory of Open Access Journals (Sweden)

    Yunfeng Dong

    2017-01-01

    Full Text Available The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM, which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM. In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.

  13. A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices

    Directory of Open Access Journals (Sweden)

    Fang Liu

    2018-01-01

    Full Text Available Wearable technology is one of the greatest applications of the Internet of Things. The popularity of wearable devices has led to a massive scale of personal (user-specific data. Generally, data holders (manufacturers of wearable devices are willing to share these data with others to get benefits. However, significant privacy concerns would arise when sharing the data with the third party in an improper manner. In this paper, we first propose a specific threat model about the data sharing process of wearable devices’ data. Then we propose a K-anonymity method based on clustering to preserve privacy of wearable IoT devices’ data and guarantee the usability of the collected data. Experiment results demonstrate the effectiveness of the proposed method.

  14. Comparison and combination of "direct" and fragment based local correlation methods: Cluster in molecules and domain based local pair natural orbital perturbation and coupled cluster theories

    Science.gov (United States)

    Guo, Yang; Becker, Ute; Neese, Frank

    2018-03-01

    Local correlation theories have been developed in two main flavors: (1) "direct" local correlation methods apply local approximation to the canonical equations and (2) fragment based methods reconstruct the correlation energy from a series of smaller calculations on subsystems. The present work serves two purposes. First, we investigate the relative efficiencies of the two approaches using the domain-based local pair natural orbital (DLPNO) approach as the "direct" method and the cluster in molecule (CIM) approach as the fragment based approach. Both approaches are applied in conjunction with second-order many-body perturbation theory (MP2) as well as coupled-cluster theory with single-, double- and perturbative triple excitations [CCSD(T)]. Second, we have investigated the possible merits of combining the two approaches by performing CIM calculations with DLPNO methods serving as the method of choice for performing the subsystem calculations. Our cluster-in-molecule approach is closely related to but slightly deviates from approaches in the literature since we have avoided real space cutoffs. Moreover, the neglected distant pair correlations in the previous CIM approach are considered approximately. Six very large molecules (503-2380 atoms) were studied. At both MP2 and CCSD(T) levels of theory, the CIM and DLPNO methods show similar efficiency. However, DLPNO methods are more accurate for 3-dimensional systems. While we have found only little incentive for the combination of CIM with DLPNO-MP2, the situation is different for CIM-DLPNO-CCSD(T). This combination is attractive because (1) the better parallelization opportunities offered by CIM; (2) the methodology is less memory intensive than the genuine DLPNO-CCSD(T) method and, hence, allows for large calculations on more modest hardware; and (3) the methodology is applicable and efficient in the frequently met cases, where the largest subsystem calculation is too large for the canonical CCSD(T) method.

  15. METHODS FOR CLUSTERING TIME SERIES DATA ACQUIRED FROM MOBILE HEALTH APPS.

    Science.gov (United States)

    Tignor, Nicole; Wang, Pei; Genes, Nicholas; Rogers, Linda; Hershman, Steven G; Scott, Erick R; Zweig, Micol; Yvonne Chan, Yu-Feng; Schadt, Eric E

    2017-01-01

    In our recent Asthma Mobile Health Study (AMHS), thousands of asthma patients across the country contributed medical data through the iPhone Asthma Health App on a daily basis for an extended period of time. The collected data included daily self-reported asthma symptoms, symptom triggers, and real time geographic location information. The AMHS is just one of many studies occurring in the context of now many thousands of mobile health apps aimed at improving wellness and better managing chronic disease conditions, leveraging the passive and active collection of data from mobile, handheld smart devices. The ability to identify patient groups or patterns of symptoms that might predict adverse outcomes such as asthma exacerbations or hospitalizations from these types of large, prospectively collected data sets, would be of significant general interest. However, conventional clustering methods cannot be applied to these types of longitudinally collected data, especially survey data actively collected from app users, given heterogeneous patterns of missing values due to: 1) varying survey response rates among different users, 2) varying survey response rates over time of each user, and 3) non-overlapping periods of enrollment among different users. To handle such complicated missing data structure, we proposed a probability imputation model to infer missing data. We also employed a consensus clustering strategy in tandem with the multiple imputation procedure. Through simulation studies under a range of scenarios reflecting real data conditions, we identified favorable performance of the proposed method over other strategies that impute the missing value through low-rank matrix completion. When applying the proposed new method to study asthma triggers and symptoms collected as part of the AMHS, we identified several patient groups with distinct phenotype patterns. Further validation of the methods described in this paper might be used to identify clinically important

  16. Evaluation of a chemical risk assessment method of South Korea for chemicals classified as carcinogenic, mutagenic or reprotoxic (CMR).

    Science.gov (United States)

    Kim, Min-Uk; Byeon, Sang-Hoon

    2017-12-12

    Chemicals were used in various fields by the development of industry and science and technology. The Chemical Hazard Risk Management (CHARM) was developed to assess the risk of chemicals in South Korea. In this study, we were to evaluate the CHARM model developed for the effective management of workplace chemicals. We used 59 carcinogenic, mutagenic or reprotoxic (CMR) materials, which are both the work environment measurement result and the usage information among the manufacturer data. The CHARM model determines the risk to human health using the exposure level (based on working environment measurements or a combination of the quantity used and chemical physical properties (e.g., fugacity and volatility)), hazard (using occupational exposure limit (OEL) or Risk phrases (R-phrases)/Hazard statements (H-statements) from the Material Safety Data Sheet (MSDS)). The risk level was lower when using the results of the work environment measurement than when applying the chemical quantity and physical properties in the exposure level evaluation method. It was evaluated as grade 4 for the CMR material in the hazard class determination. The risk assessment method by R-phrases was evaluated more conservatively than the risk assessment method by OEL. And the risk assessment method by H-statements was evaluated more conservatively than the risk assessment method by R-phrases. The CHARM model was gradually conservatively assessed as it proceeded in the next step without quantitative information for individual workplaces. The CHARM is expected to help identify the risk if the hazards and exposure levels of chemicals were identified in individual workplaces. For CMR substances, although CHARM is highly evaluated for hazards, the risk is assessed to be low if exposure levels are assessed low. When evaluating the risk of highly hazardous chemicals such as CMR substances, we believe the model should be adapted to be more conservative and classify these as higher risk. This work is

  17. The cosmological analysis of X-ray cluster surveys - I. A new method for interpreting number counts

    Science.gov (United States)

    Clerc, N.; Pierre, M.; Pacaud, F.; Sadibekova, T.

    2012-07-01

    We present a new method aimed at simplifying the cosmological analysis of X-ray cluster surveys. It is based on purely instrumental observable quantities considered in a two-dimensional X-ray colour-magnitude diagram (hardness ratio versus count rate). The basic principle is that even in rather shallow surveys, substantial information on cluster redshift and temperature is present in the raw X-ray data and can be statistically extracted; in parallel, such diagrams can be readily predicted from an ab initio cosmological modelling. We illustrate the methodology for the case of a 100-deg2XMM survey having a sensitivity of ˜10-14 erg s-1 cm-2 and fit at the same time, the survey selection function, the cluster evolutionary scaling relations and the cosmology; our sole assumption - driven by the limited size of the sample considered in the case study - is that the local cluster scaling relations are known. We devote special attention to the realistic modelling of the count-rate measurement uncertainties and evaluate the potential of the method via a Fisher analysis. In the absence of individual cluster redshifts, the count rate and hardness ratio (CR-HR) method appears to be much more efficient than the traditional approach based on cluster counts (i.e. dn/dz, requiring redshifts). In the case where redshifts are available, our method performs similar to the traditional mass function (dn/dM/dz) for the purely cosmological parameters, but constrains better parameters defining the cluster scaling relations and their evolution. A further practical advantage of the CR-HR method is its simplicity: this fully top-down approach totally bypasses the tedious steps consisting in deriving cluster masses from X-ray temperature measurements.

  18. Comparison of three methods for the estimation of cross-shock electric potential using Cluster data

    Directory of Open Access Journals (Sweden)

    A. P. Dimmock

    2011-05-01

    Full Text Available Cluster four point measurements provide a comprehensive dataset for the separation of temporal and spatial variations, which is crucial for the calculation of the cross shock electrostatic potential using electric field measurements. While Cluster is probably the most suited among present and past spacecraft missions to provide such a separation at the terrestrial bow shock, it is far from ideal for a study of the cross shock potential, since only 2 components of the electric field are measured in the spacecraft spin plane. The present paper is devoted to the comparison of 3 different techniques that can be used to estimate the potential with this limitation. The first technique is the estimate taking only into account the projection of the measured components onto the shock normal. The second uses the ideal MHD condition E·B = 0 to estimate the third electric field component. The last method is based on the structure of the electric field in the Normal Incidence Frame (NIF for which only the potential component along the shock normal and the motional electric field exist. All 3 approaches are used to estimate the potential for a single crossing of the terrestrial bow shock that took place on the 31 March 2001. Surprisingly all three methods lead to the same order of magnitude for the cross shock potential. It is argued that the third method must lead to more reliable results. The effect of the shock normal inaccuracy is investigated for this particular shock crossing. The resulting electrostatic potential appears too high in comparison with the theoretical results for low Mach number shocks. This shows the variability of the potential, interpreted in the frame of the non-stationary shock model.

  19. Why so GLUMM? Detecting depression clusters through graphing lifestyle-environs using machine-learning methods (GLUMM).

    Science.gov (United States)

    Dipnall, J F; Pasco, J A; Berk, M; Williams, L J; Dodd, S; Jacka, F N; Meyer, D

    2017-01-01

    Key lifestyle-environ risk factors are operative for depression, but it is unclear how risk factors cluster. Machine-learning (ML) algorithms exist that learn, extract, identify and map underlying patterns to identify groupings of depressed individuals without constraints. The aim of this research was to use a large epidemiological study to identify and characterise depression clusters through "Graphing lifestyle-environs using machine-learning methods" (GLUMM). Two ML algorithms were implemented: unsupervised Self-organised mapping (SOM) to create GLUMM clusters and a supervised boosted regression algorithm to describe clusters. Ninety-six "lifestyle-environ" variables were used from the National health and nutrition examination study (2009-2010). Multivariate logistic regression validated clusters and controlled for possible sociodemographic confounders. The SOM identified two GLUMM cluster solutions. These solutions contained one dominant depressed cluster (GLUMM5-1, GLUMM7-1). Equal proportions of members in each cluster rated as highly depressed (17%). Alcohol consumption and demographics validated clusters. Boosted regression identified GLUMM5-1 as more informative than GLUMM7-1. Members were more likely to: have problems sleeping; unhealthy eating; ≤2 years in their home; an old home; perceive themselves underweight; exposed to work fumes; experienced sex at ≤14 years; not perform moderate recreational activities. A positive relationship between GLUMM5-1 (OR: 7.50, Pdepression was found, with significant interactions with those married/living with partner (P=0.001). Using ML based GLUMM to form ordered depressive clusters from multitudinous lifestyle-environ variables enabled a deeper exploration of the heterogeneous data to uncover better understandings into relationships between the complex mental health factors. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  20. Hadron formation in a non-ideal quark gluon plasma using Mayer's method of cluster expansion

    International Nuclear Information System (INIS)

    Prasanth, J.P.; Bannur, Vishnu M.

    2015-01-01

    This work investigates the applicability of using the Mayer's cluster expansion method to derive the equation of state (EoS) of the quark-antiquark plasma. Dissociation of heavier hadrons in QGP is studied. The possibility of the existence of quarkonium after deconfinement at higher temperature than the critical temperature T > T c is investigated. The EoS has been studied by calculating second and third cluster integrals. The results are compared and discussed with available works. (author)

  1. Wireless Chemical Sensor and Sensing Method for Use Therewith

    Science.gov (United States)

    Woodard, Stanley E. (Inventor); Oglesby, Donald M. (Inventor); Taylor, Bryant D. (Inventor)

    2016-01-01

    A wireless chemical sensor includes an electrical conductor and a material separated therefrom by an electric insulator. The electrical conductor is an unconnected open-circuit shaped for storage of an electric field and a magnetic field. In the presence of a time-varying magnetic field, the first electrical conductor resonates to generate harmonic electric and magnetic field responses. The material is positioned at a location lying within at least one of the electric and magnetic field responses so-generated. The material changes in electrical conductivity in the presence of a chemical-of-interest.

  2. The potential of clustering methods to define intersection test scenarios: Assessing real-life performance of AEB.

    Science.gov (United States)

    Sander, Ulrich; Lubbe, Nils

    2018-04-01

    Intersection accidents are frequent and harmful. The accident types 'straight crossing path' (SCP), 'left turn across path - oncoming direction' (LTAP/OD), and 'left-turn across path - lateral direction' (LTAP/LD) represent around 95% of all intersection accidents and one-third of all police-reported car-to-car accidents in Germany. The European New Car Assessment Program (Euro NCAP) have announced that intersection scenarios will be included in their rating from 2020; however, how these scenarios are to be tested has not been defined. This study investigates whether clustering methods can be used to identify a small number of test scenarios sufficiently representative of the accident dataset to evaluate Intersection Automated Emergency Braking (AEB). Data from the German In-Depth Accident Study (GIDAS) and the GIDAS-based Pre-Crash Matrix (PCM) from 1999 to 2016, containing 784 SCP and 453 LTAP/OD accidents, were analyzed with principal component methods to identify variables that account for the relevant total variances of the sample. Three different methods for data clustering were applied to each of the accident types, two similarity-based approaches, namely Hierarchical Clustering (HC) and Partitioning Around Medoids (PAM), and the probability-based Latent Class Clustering (LCC). The optimum number of clusters was derived for HC and PAM with the silhouette method. The PAM algorithm was both initiated with random start medoid selection and medoids from HC. For LCC, the Bayesian Information Criterion (BIC) was used to determine the optimal number of clusters. Test scenarios were defined from optimal cluster medoids weighted by their real-life representation in GIDAS. The set of variables for clustering was further varied to investigate the influence of variable type and character. We quantified how accurately each cluster variation represents real-life AEB performance using pre-crash simulations with PCM data and a generic algorithm for AEB intervention. The

  3. Noniterative Multireference Coupled Cluster Methods on Heterogeneous CPU-GPU Systems

    Energy Technology Data Exchange (ETDEWEB)

    Bhaskaran-Nair, Kiran; Ma, Wenjing; Krishnamoorthy, Sriram; Villa, Oreste; van Dam, Hubertus JJ; Apra, Edoardo; Kowalski, Karol

    2013-04-09

    A novel parallel algorithm for non-iterative multireference coupled cluster (MRCC) theories, which merges recently introduced reference-level parallelism (RLP) [K. Bhaskaran-Nair, J.Brabec, E. Aprà, H.J.J. van Dam, J. Pittner, K. Kowalski, J. Chem. Phys. 137, 094112 (2012)] with the possibility of accelerating numerical calculations using graphics processing unit (GPU) is presented. We discuss the performance of this algorithm on the example of the MRCCSD(T) method (iterative singles and doubles and perturbative triples), where the corrections due to triples are added to the diagonal elements of the MRCCSD (iterative singles and doubles) effective Hamiltonian matrix. The performance of the combined RLP/GPU algorithm is illustrated on the example of the Brillouin-Wigner (BW) and Mukherjee (Mk) state-specific MRCCSD(T) formulations.

  4. Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

    Science.gov (United States)

    Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

    2010-07-01

    The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

  5. Equation-of-motion coupled cluster method for high spin double electron attachment calculations

    Energy Technology Data Exchange (ETDEWEB)

    Musiał, Monika, E-mail: musial@ich.us.edu.pl; Lupa, Łukasz; Kucharski, Stanisław A. [Institute of Chemistry, University of Silesia, Szkolna 9, 40-006 Katowice (Poland)

    2014-03-21

    The new formulation of the equation-of-motion (EOM) coupled cluster (CC) approach applicable to the calculations of the double electron attachment (DEA) states for the high spin components is proposed. The new EOM equations are derived for the high spin triplet and quintet states. In both cases the new equations are easier to solve but the substantial simplification is observed in the case of quintets. Out of 21 diagrammatic terms contributing to the standard DEA-EOM-CCSDT equations for the R{sub 2} and R{sub 3} amplitudes only four terms survive contributing to the R{sub 3} part. The implemented method has been applied to the calculations of the excited states (singlets, triplets, and quintets) energies of the carbon and silicon atoms and potential energy curves for selected states of the Na{sub 2} (triplets) and B{sub 2} (quintets) molecules.

  6. Novel strategy to implement active-space coupled-cluster methods

    Science.gov (United States)

    Rolik, Zoltán; Kállay, Mihály

    2018-03-01

    A new approach is presented for the efficient implementation of coupled-cluster (CC) methods including higher excitations based on a molecular orbital space partitioned into active and inactive orbitals. In the new framework, the string representation of amplitudes and intermediates is used as long as it is beneficial, but the contractions are evaluated as matrix products. Using a new diagrammatic technique, the CC equations are represented in a compact form due to the string notations we introduced. As an application of these ideas, a new automated implementation of the single-reference-based multi-reference CC equations is presented for arbitrary excitation levels. The new program can be considered as an improvement over the previous implementations in many respects; e.g., diagram contributions are evaluated by efficient vectorized subroutines. Timings for test calculations for various complete active-space problems are presented. As an application of the new code, the weak interactions in the Be dimer were studied.

  7. Application of the cluster variation method to ordering in an interstitital solid solution

    DEFF Research Database (Denmark)

    Pekelharing, Marjon I.; Böttger, Amarante; Somers, Marcel A. J.

    1999-01-01

    The tetrahedron approximation of the cluster variation method (CVM) was applied to describe the ordering on the fcc interstitial sublattice of gamma-Fe[N] and gamma'-Fe4N1-x. A Lennard-Jones potential was used to describe the dominantly strain-induced interactions, caused by misfitting of the N...... atoms in the interstitial octahedral sites. The gamma-Fe[N]/gamma'-Fe4N1-x miscibility gap, short range ordering (SRO), and long-range ordering (LRO) of nitrogen in gamma-Fe[N] and gamma'-Fe4N1-x, respectively, and lattice parameters of gamma and gamm' were calculated. For the first time, N distribution...... parameters,as calculated by CVM, were compared directly to Mössbauer data for specific surroundings of Fe atoms....

  8. Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography.

    Science.gov (United States)

    Waugh, William; Allen, John; Wightman, James; Sims, Andrew J; Beale, Thomas A W

    2018-01-01

    Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.

  9. Aperture-Tolerant, Chemical-Based Methods to Reduce Channeling

    Energy Technology Data Exchange (ETDEWEB)

    Randall S. Seright

    2007-09-30

    This final technical progress report describes work performed from October 1, 2004, through May 16, 2007, for the project, 'Aperture-Tolerant, Chemical-Based Methods to Reduce Channeling'. We explored the potential of pore-filling gels for reducing excess water production from both fractured and unfractured production wells. Several gel formulations were identified that met the requirements--i.e., providing water residual resistance factors greater than 2,000 and ultimate oil residual resistance factors (F{sub rro}) of 2 or less. Significant oil throughput was required to achieve low F{sub rro} values, suggesting that gelant penetration into porous rock must be small (a few feet or less) for existing pore-filling gels to provide effective disproportionate permeability reduction. Compared with adsorbed polymers and weak gels, strong pore-filling gels can provide greater reliability and behavior that is insensitive to the initial rock permeability. Guidance is provided on where relative-permeability-modification/disproportionate-permeability-reduction treatments can be successfully applied for use in either oil or gas production wells. When properly designed and executed, these treatments can be successfully applied to a limited range of oilfield excessive-water-production problems. We examined whether gel rheology can explain behavior during extrusion through fractures. The rheology behavior of the gels tested showed a strong parallel to the results obtained from previous gel extrusion experiments. However, for a given aperture (fracture width or plate-plate separation), the pressure gradients measured during the gel extrusion experiments were much higher than anticipated from rheology measurements. Extensive experiments established that wall slip and first normal stress difference were not responsible for the pressure gradient discrepancy. To explain the discrepancy, we noted that the aperture for gel flow (for mobile gel wormholing through concentrated

  10. A New Method to Constrain Supernova Fractions Using X-ray Observations of Clusters of Galaxies

    Science.gov (United States)

    Bulbul, Esra; Smith, Randall K.; Loewenstein, Michael

    2012-01-01

    Supernova (SN) explosions enrich the intracluster medium (ICM) both by creating and dispersing metals. We introduce a method to measure the number of SNe and relative contribution of Type Ia supernovae (SNe Ia) and core-collapse supernovae (SNe cc) by directly fitting X-ray spectral observations. The method has been implemented as an XSPEC model called snapec. snapec utilizes a single-temperature thermal plasma code (apec) to model the spectral emission based on metal abundances calculated using the latest SN yields from SN Ia and SN cc explosion models. This approach provides a self-consistent single set of uncertainties on the total number of SN explosions and relative fraction of SN types in the ICM over the cluster lifetime by directly allowing these parameters to be determined by SN yields provided by simulations. We apply our approach to XMM-Newton European Photon Imaging Camera (EPIC), Reflection Grating Spectrometer (RGS), and 200 ks simulated Astro-H observations of a cooling flow cluster, A3112.We find that various sets of SN yields present in the literature produce an acceptable fit to the EPIC and RGS spectra of A3112. We infer that 30.3% plus or minus 5.4% to 37.1% plus or minus 7.1% of the total SN explosions are SNe Ia, and the total number of SN explosions required to create the observed metals is in the range of (1.06 plus or minus 0.34) x 10(exp 9), to (1.28 plus or minus 0.43) x 10(exp 9), fromsnapec fits to RGS spectra. These values may be compared to the enrichment expected based on well-established empirically measured SN rates per star formed. The proportions of SNe Ia and SNe cc inferred to have enriched the ICM in the inner 52 kiloparsecs of A3112 is consistent with these specific rates, if one applies a correction for the metals locked up in stars. At the same time, the inferred level of SN enrichment corresponds to a star-to-gas mass ratio that is several times greater than the 10% estimated globally for clusters in the A3112 mass range.

  11. Minimizing the Free Energy: A Computer Method for Teaching Chemical Equilibrium Concepts.

    Science.gov (United States)

    Heald, Emerson F.

    1978-01-01

    Presents a computer method for teaching chemical equilibrium concepts using material balance conditions and the minimization of the free energy. Method for the calculation of chemical equilibrium, the computer program used to solve equilibrium problems and applications of the method are also included. (HM)

  12. Methods and tools for sustainable chemical process design

    DEFF Research Database (Denmark)

    Loureiro da Costa Lira Gargalo, Carina; Chairakwongsa, Siwanat; Quaglia, Alberto

    2015-01-01

    As the pressure on chemical and biochemical processes to achieve a more sustainable performance increases, the need to define a systematic and holistic way to accomplish this is becoming more urgent. In this chapter, a multilevel computer-aided framework for systematic design of more sustainable...

  13. Current methods in risk assessment of genotoxic chemicals.

    Science.gov (United States)

    Cartus, Alexander; Schrenk, Dieter

    2017-08-01

    Chemical contaminants and residues are undesired chemicals occurring in consumer products such as food and drugs, at the workplace and in the environment, i.e. in air, soil and water. These compounds can be detected even at very low concentrations and lead frequently to considerable concerns among consumers and in the media. Thus it is a major challenge for modern toxicology to provide transparent and versatile tools for the risk assessment of such compounds in particular with respect to human health. Well-known examples of toxic contaminants are dioxins or mercury (in the environment), mycotoxins (from infections by molds) or acrylamide (from thermal treatment of food). The process of toxicological risk assessment of such chemicals is based on i) the knowledge of their contents in food, air, water etc., ii) the routes and extent of exposure of humans, iii) the toxicological properties of the compound, and, iv) its mode(s) of action. In this process quantitative dose-response relationships, usually in experimental animals, are of outstanding importance. For a successful risk assessment, in particular of genotoxic chemicals, several conditions and models such as the Margin of Exposure (MoE) approach or the Threshold of Toxicological Concern (TTC) concept exist, which will be discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Effects of different chemical materials and cultural methods on ...

    African Journals Online (AJOL)

    reading 6

    2011-10-27

    Oct 27, 2011 ... which accounts for 53% of wheat production in China and about 15% of the total ... environment as it is mainly made from chemical mate- rials. ... yield and yield components in harvest in both years were deter- mined. The data were subjected to analyses of variance (ANOVA) ..... Long-term stability of.

  15. Device and method for enhanced collection and assay of chemicals with high surface area ceramic

    Science.gov (United States)

    Addleman, Raymond S.; Li, Xiaohong Shari; Chouyyok, Wilaiwan; Cinson, Anthony D.; Bays, John T.; Wallace, Krys

    2016-02-16

    A method and device for enhanced capture of target analytes is disclosed. This invention relates to collection of chemicals for separations and analysis. More specifically, this invention relates to a solid phase microextraction (SPME) device having better capability for chemical collection and analysis. This includes better physical stability, capacity for chemical collection, flexible surface chemistry and high affinity for target analyte.

  16. CHEMICAL ABUNDANCE EVIDENCE OF ENDURING HIGH STAR FORMATION RATES IN AN EARLY-TYPE GALAXY: HIGH [Ca/Fe] IN NGC 5128 GLOBULAR CLUSTERS

    International Nuclear Information System (INIS)

    Colucci, Janet E.; Durán, María Fernanda; Bernstein, Rebecca A.; McWilliam, Andrew

    2013-01-01

    We present [Fe/H], ages, and Ca abundances for an initial sample of 10 globular clusters in NGC 5128 obtained from high-resolution, high signal-to-noise ratio echelle spectra of their integrated light. All abundances and ages are obtained using our original technique for high-resolution integrated light abundance analysis of globular clusters. The clusters have a range in [Fe/H] between –1.6 and –0.2. In this sample, the average [Ca/Fe] for clusters with [Fe/H] <–0.4 is +0.37 ± 0.07, while the average [Ca/Fe] in our Milky Way (MW) and M31 GC samples is +0.29 ± 0.09 and +0.24 ± 0.10, respectively. This may imply a more rapid chemical enrichment history for NGC 5128 than for either the MW or M31. This sample provides the first quantitative picture of the chemical history of NGC 5128 that is directly comparable to what is available for the MW. Data presented here were obtained with the MIKE echelle spectrograph on the Magellan Clay Telescope

  17. CHEMICAL ABUNDANCE EVIDENCE OF ENDURING HIGH STAR FORMATION RATES IN AN EARLY-TYPE GALAXY: HIGH [Ca/Fe] IN NGC 5128 GLOBULAR CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Colucci, Janet E.; Duran, Maria Fernanda; Bernstein, Rebecca A. [Department of Astronomy and Astrophysics, 1156 High Street, UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 (United States); McWilliam, Andrew, E-mail: jcolucci@ucolick.org [Observatories of the Carnegie Institute of Washington, 813 Santa Barbara Street, Pasadena, CA 91101-1292 (United States)

    2013-08-20

    We present [Fe/H], ages, and Ca abundances for an initial sample of 10 globular clusters in NGC 5128 obtained from high-resolution, high signal-to-noise ratio echelle spectra of their integrated light. All abundances and ages are obtained using our original technique for high-resolution integrated light abundance analysis of globular clusters. The clusters have a range in [Fe/H] between -1.6 and -0.2. In this sample, the average [Ca/Fe] for clusters with [Fe/H] <-0.4 is +0.37 {+-} 0.07, while the average [Ca/Fe] in our Milky Way (MW) and M31 GC samples is +0.29 {+-} 0.09 and +0.24 {+-} 0.10, respectively. This may imply a more rapid chemical enrichment history for NGC 5128 than for either the MW or M31. This sample provides the first quantitative picture of the chemical history of NGC 5128 that is directly comparable to what is available for the MW. Data presented here were obtained with the MIKE echelle spectrograph on the Magellan Clay Telescope.

  18. Chemical Abundance Evidence of Enduring High Star Formation Rates in an Early-type Galaxy: High [Ca/Fe] in NGC 5128 Globular Clusters

    Science.gov (United States)

    Colucci, Janet E.; Fernanda Durán, María; Bernstein, Rebecca A.; McWilliam, Andrew

    2013-08-01

    We present [Fe/H], ages, and Ca abundances for an initial sample of 10 globular clusters in NGC 5128 obtained from high-resolution, high signal-to-noise ratio echelle spectra of their integrated light. All abundances and ages are obtained using our original technique for high-resolution integrated light abundance analysis of globular clusters. The clusters have a range in [Fe/H] between -1.6 and -0.2. In this sample, the average [Ca/Fe] for clusters with [Fe/H] <-0.4 is +0.37 ± 0.07, while the average [Ca/Fe] in our Milky Way (MW) and M31 GC samples is +0.29 ± 0.09 and +0.24 ± 0.10, respectively. This may imply a more rapid chemical enrichment history for NGC 5128 than for either the MW or M31. This sample provides the first quantitative picture of the chemical history of NGC 5128 that is directly comparable to what is available for the MW. Data presented here were obtained with the MIKE echelle spectrograph on the Magellan Clay Telescope. This Letter includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

  19. Consolidation of the formation sand by chemical methods

    Directory of Open Access Journals (Sweden)

    Mariana Mihočová

    2006-10-01

    Full Text Available The sand control by consolidation involves the process of injecting chemicals into the naturally unconsolidated formation to provide an in situ grain-to-grain cementation. The sand consolidation chemicals are available for some 30 years. Several types of consolidating material were tried. Presently available systems utilize solidified plastics to provide the cementation. These systems include phenol resin, phenol-formaldehyde, epoxy, furan and phenolic-furfuryl.The sand consolidation with the steam injection is a novel technique. This process provides a highly alkaline liquid phase and temperatures to 300 °C to geochemically create cements by interacting with the dirty sand.While the formation consolidation has widely applied, our experience has proved a high level of success.

  20. Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method

    Science.gov (United States)

    Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui

    2018-05-01

    In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.

  1. Using deuterated PAH amendments to validate chemical extraction methods to predict PAH bioavailability in soils

    International Nuclear Information System (INIS)

    Gomez-Eyles, Jose L.; Collins, Chris D.; Hodson, Mark E.

    2011-01-01

    Validating chemical methods to predict bioavailable fractions of polycyclic aromatic hydrocarbons (PAHs) by comparison with accumulation bioassays is problematic. Concentrations accumulated in soil organisms not only depend on the bioavailable fraction but also on contaminant properties. A historically contaminated soil was freshly spiked with deuterated PAHs (dPAHs). dPAHs have a similar fate to their respective undeuterated analogues, so chemical methods that give good indications of bioavailability should extract the fresh more readily available dPAHs and historic more recalcitrant PAHs in similar proportions to those in which they are accumulated in the tissues of test organisms. Cyclodextrin and butanol extractions predicted the bioavailable fraction for earthworms (Eisenia fetida) and plants (Lolium multiflorum) better than the exhaustive extraction. The PAHs accumulated by earthworms had a larger dPAH:PAH ratio than that predicted by chemical methods. The isotope ratio method described here provides an effective way of evaluating other chemical methods to predict bioavailability. - Research highlights: → Isotope ratios can be used to evaluate chemical methods to predict bioavailability. → Chemical methods predicted bioavailability better than exhaustive extractions. → Bioavailability to earthworms was still far from that predicted by chemical methods. - A novel method using isotope ratios to assess the ability of chemical methods to predict PAH bioavailability to soil biota.

  2. Using deuterated PAH amendments to validate chemical extraction methods to predict PAH bioavailability in soils

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Eyles, Jose L., E-mail: j.l.gomezeyles@reading.ac.uk [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom); Collins, Chris D.; Hodson, Mark E. [University of Reading, School of Human and Environmental Sciences, Soil Research Centre, Reading, RG6 6DW Berkshire (United Kingdom)

    2011-04-15

    Validating chemical methods to predict bioavailable fractions of polycyclic aromatic hydrocarbons (PAHs) by comparison with accumulation bioassays is problematic. Concentrations accumulated in soil organisms not only depend on the bioavailable fraction but also on contaminant properties. A historically contaminated soil was freshly spiked with deuterated PAHs (dPAHs). dPAHs have a similar fate to their respective undeuterated analogues, so chemical methods that give good indications of bioavailability should extract the fresh more readily available dPAHs and historic more recalcitrant PAHs in similar proportions to those in which they are accumulated in the tissues of test organisms. Cyclodextrin and butanol extractions predicted the bioavailable fraction for earthworms (Eisenia fetida) and plants (Lolium multiflorum) better than the exhaustive extraction. The PAHs accumulated by earthworms had a larger dPAH:PAH ratio than that predicted by chemical methods. The isotope ratio method described here provides an effective way of evaluating other chemical methods to predict bioavailability. - Research highlights: > Isotope ratios can be used to evaluate chemical methods to predict bioavailability. > Chemical methods predicted bioavailability better than exhaustive extractions. > Bioavailability to earthworms was still far from that predicted by chemical methods. - A novel method using isotope ratios to assess the ability of chemical methods to predict PAH bioavailability to soil biota.

  3. Method of heat decomposition for chemical decontaminating resin waste

    International Nuclear Information System (INIS)

    Kikuchi, Akira.

    1988-01-01

    Purpose: To make resin wastes into non-deleterious state, discharge them into a resin waste storage tank of existent radioactive waste processing facility and store and dispose them. Constitution: In the processing of chemical decontaminating resin wastes, iron exchange resins adsorbing chemical decontaminating agents comprising a solution of citric acid, oxalic acid, formic acid and EDTA alone or as a mixture of them are heated to dry, thermally decomposed and then separated from the ion exchange resins. That is, the main ingredients of the chemical decontaminating agents are heat-decomposed when heated and dried at about 250 deg C in air and converted into non-toxic gases such as CO, CO 2 , NO, NO 2 or H 2 O. Further, since combustion or carbonization of the basic materials for the resin is not caused at such a level of temperature, the resin wastes removed with organic acid and chelating agents are transferred to an existent resin waste storage tank and stored therein. In this way, facility cost and radiation exposure can remarkably be decreased. (Kamimura, M.)

  4. Evolution of Chemical Diversity in a Group of Non-Reduced Polyketide Gene Clusters: Using Phylogenetics to Inform the Search for Novel Fungal Natural Products

    Directory of Open Access Journals (Sweden)

    Kurt Throckmorton

    2015-09-01

    Full Text Available Fungal polyketides are a diverse class of natural products, or secondary metabolites (SMs, with a wide range of bioactivities often associated with toxicity. Here, we focus on a group of non-reducing polyketide synthases (NR-PKSs in the fungal phylum Ascomycota that lack a thioesterase domain for product release, group V. Although widespread in ascomycete taxa, this group of NR-PKSs is notably absent in the mycotoxigenic genus Fusarium and, surprisingly, found in genera not known for their secondary metabolite production (e.g., the mycorrhizal genus Oidiodendron, the powdery mildew genus Blumeria, and the causative agent of white-nose syndrome in bats, Pseudogymnoascus destructans. This group of NR-PKSs, in association with the other enzymes encoded by their gene clusters, produces a variety of different chemical classes including naphthacenediones, anthraquinones, benzophenones, grisandienes, and diphenyl ethers. We discuss the modification of and transitions between these chemical classes, the requisite enzymes, and the evolution of the SM gene clusters that encode them. Integrating this information, we predict the likely products of related but uncharacterized SM clusters, and we speculate upon the utility of these classes of SMs as virulence factors or chemical defenses to various plant, animal, and insect pathogens, as well as mutualistic fungi.

  5. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    OpenAIRE

    Qiao Wei; Li Ying; Wu Zhong-Hai

    2017-01-01

    Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

  6. Theoretical characterization of the F(2)O(3) molecule by coupled-cluster methods.

    Science.gov (United States)

    Huang, Ming-Ju; Watts, John D

    2010-09-23

    Coupled-cluster calculations with extended basis sets that include noniterative connected triple excitations (CCSD(T)) have been used to study the FOOOF isomer of F(2)O(3). Second-order Moller-Plessett perturbation theory (MP2) and density-functional theory (B3LYP functional) calculations have also been performed for comparison. Two local minima of similar energy, namely, conformers of C(2) and C(s) symmetry have been located. Structures, harmonic vibrational frequencies, and standard enthalpies and free energies of formation have been calculated. The calculated bond lengths of F(2)O(3) are more characteristic of those in F(2)O and a "normal" peroxide than the unusual bond lengths in F(2)O(2). Both conformers have equal F-O and O-O bond lengths, contrary to a recent suggestion of an unsymmetrical structure. The harmonic vibrational frequencies can aid possible identification of gaseous F(2)O(3). The calculated Δ(f)H° and Δ(f)G° are 110 and 173 kJ mol(-1), respectively. These values are based on extrapolation of CCSD(T) results with augmented triple- and quadruple-ζ basis sets and are expected to be within chemical accuracy (i.e., 1 kcal mol(-1) or 4 kJ mol(-1)). F(2)O(3) is calculated to be stable to decomposition to either FO + FOO or F(2) + O(3), but unstable to decomposition to its elements, to F(2)O(2) + (1)/(2)O(2), and to F(2)O + O(2).

  7. Development of a Benchtop Baking Method for Chemically Leavened Crackers

    Science.gov (United States)

    Traditionally, the baking performance of soft wheat flours has been evaluated by well-established benchtop cookie-baking methods. In contrast, a benchtop cracker-baking method has not been widely explored or implemented as an official method, due to hurdles including the difficulty in finding ideal...

  8. Dancoff factors with partial neutrons absorption in cluster geometry by the direct method

    International Nuclear Information System (INIS)

    Rodrigues, Leticia Jenisch

    2007-01-01

    Accurate analysis of resonance absorption in heterogeneous systems is essential in problems like criticality, breeding ratios and fuel depletion calculations. In compact arrays of fuel rods, resonance absorption is strongly affected by the Dancoff factor, defined in mis study as the probability that a neutron emitted from the surface of a fuel element, enters another fuel element without any collusion in the moderator or cladding. In fact, in the most practical cases of irregular cells, it is observed that inaccuracies in computing both Grey and Black Dancoff factors, i.e. for partially and perfectly absorbing fuel rods, can lead to considerable errors in the calculated values of such integral quantities. For this reason, much effort has been made in the past decades to further improve the models for calculating Dancoff factors, a task that has been accomplished in connection with the development of faster computers. In the WIMS code, Black Dancoff factors based on the above mentioned collusion probability definition are computed in cluster geometry, for each one of the symmetrically distinct fuel pin positions in the cell. Sets of equally-spaced parallel lines are drawn in subroutine PIJ, at a number of discrete equally-incremented azimuthal angles, covering the whole system and forming a mesh over which the in-plane integrations of the Bickley functions are carried out by simple trapezoidal rule, leading to the first-flight collusion matrices. Although fast, the method in PIJ is inefficient, since the constructed mesh does not depended on the system details, so that regions of small relative volumes are crossed out by relatively few lines, which affects the convergence of the calculated probabilities. A new routine (PIJM) was then created to incorporate a more efficient integration scheme considering each system region individually, minimizing convergence problems and reducing the number of neutron track lines required in the in-plane integrations for any given

  9. Chemical and ecological control methods for Epitrix spp.

    Directory of Open Access Journals (Sweden)

    A. G. S. Cuthbertson

    2015-01-01

    Full Text Available Very little information exists in regards to the control options available for potato flea beetles, Epitrix spp. This short review covers both chemical and ecological options currently available for control of Epitrix spp. Synthetic pyrethroids are the weapon of choice for the beetles. However, the impetus in integrated pest management is to do timely (early-season applications with something harsh which will give long-term protection at a time when there are not a lot of beneficials in the field. Finding the balance for control of Epitrix spp. is proving difficult.

  10. Metal-assisted chemical etch porous silicon formation method

    Science.gov (United States)

    Li, Xiuling; Bohn, Paul W.; Sweedler, Jonathan V.

    2004-09-14

    A thin discontinuous layer of metal such as Au, Pt, or Au/Pd is deposited on a silicon surface. The surface is then etched in a solution including HF and an oxidant for a brief period, as little as a couple seconds to one hour. A preferred oxidant is H.sub.2 O.sub.2. Morphology and light emitting properties of porous silicon can be selectively controlled as a function of the type of metal deposited, Si doping type, silicon doping level, and/or etch time. Electrical assistance is unnecessary during the chemical etching of the invention, which may be conducted in the presence or absence of illumination.

  11. Method for separating the isotopes of a chemical element

    International Nuclear Information System (INIS)

    Devienne, F.M.

    1977-01-01

    A beam of positive or negative primary ions of at least one compound of a chemical element is accelerated in order to pass through collision boxes placed in series. As a result of inelastic collisions of the ions with the molecules of a neutral target gas within each collision box, a given percentage of primary ions is dissociated into at least two fragments, one of which is a secondary ion in the form of at least two isotopic species. The collision boxes are brought to a potential V 2 so as to trap preferentially one isotopic species which is condensed within each box. 15 claims, 4 figures

  12. Chemical Compositions of Stars in the Globular Cluster NGC 3201: Tracers of Multi-Epoch Star Formation

    Science.gov (United States)

    Simmerer, Jennifer A.; Ivans, I. I.; Filler, D.

    2012-01-01

    The retrograde halo globular cluster NGC 3201 contains stars of substantially different iron abundance ([Fe/H]), a property that puts it at odds with the vast majority of the Galactic cluster system. Though its unusual orbit prompted speculation that NGC 3201 was the remnant of a captured object, much like the multi-metallicity globular cluster Omega Centauri, NGC 3201 is much less massive than Omega Centauri and all of the other halo globular clusters that have internal metallicity variations. We present the abundances of 21 elements in 24 red giant branch stars in NGC 3201 based on high-resolution (R 40,000), high signal-to-noise (S/N 70) spectra. We find that the detailed abundance pattern of NGC 3201 is unique amongst multi-metallicity halo clusters. Unlike M22, Omega Centauri, and NGC 1851, neither metal-poor nor metal-rich stars show any evidence of s-process enrichment (a product of the advanced evolution of low- and intermediate-mass stars). We find that while Na, O, and Al vary from star to star as is typical in globular clusters, there is no systematic difference between the abundance pattern in the metal-poor cluster stars and that of the metal-rich cluster stars. Furthermore, we find that the metallicity variations in NGC 3201 are independent of the well-known Na-O anticorrelation, which separates it from every other multi-metallicity cluster. In the context of a multi-episode star formation model, this implies that NGC 3201 began life with the [Fe/H] variations we measure now.

  13. An efficient implementation of parallel molecular dynamics method on SMP cluster architecture

    International Nuclear Information System (INIS)

    Suzuki, Masaaki; Okuda, Hiroshi; Yagawa, Genki

    2003-01-01

    The authors have applied MPI/OpenMP hybrid parallel programming model to parallelize a molecular dynamics (MD) method on a symmetric multiprocessor (SMP) cluster architecture. In that architecture, it can be expected that the hybrid parallel programming model, which uses the message passing library such as MPI for inter-SMP node communication and the loop directive such as OpenMP for intra-SNP node parallelization, is the most effective one. In this study, the parallel performance of the hybrid style has been compared with that of conventional flat parallel programming style, which uses only MPI, both in cases the fast multipole method (FMM) is employed for computing long-distance interactions and that is not employed. The computer environments used here are Hitachi SR8000/MPP placed at the University of Tokyo. The results of calculation are as follows. Without FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 90% with the hybrid style, 75% with the flat-MPI style for MD simulation with 33,402 atoms. With FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 60% with the hybrid style, 48% with the flat-MPI style for MD simulation with 117,649 atoms. (author)

  14. Comparison of Three Plot Selection Methods for Estimating Change in Temporally Variable, Spatially Clustered Populations.

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, William L. [Bonneville Power Administration, Portland, OR (US). Environment, Fish and Wildlife

    2001-07-01

    Monitoring population numbers is important for assessing trends and meeting various legislative mandates. However, sampling across time introduces a temporal aspect to survey design in addition to the spatial one. For instance, a sample that is initially representative may lose this attribute if there is a shift in numbers and/or spatial distribution in the underlying population that is not reflected in later sampled plots. Plot selection methods that account for this temporal variability will produce the best trend estimates. Consequently, I used simulation to compare bias and relative precision of estimates of population change among stratified and unstratified sampling designs based on permanent, temporary, and partial replacement plots under varying levels of spatial clustering, density, and temporal shifting of populations. Permanent plots produced more precise estimates of change than temporary plots across all factors. Further, permanent plots performed better than partial replacement plots except for high density (5 and 10 individuals per plot) and 25% - 50% shifts in the population. Stratified designs always produced less precise estimates of population change for all three plot selection methods, and often produced biased change estimates and greatly inflated variance estimates under sampling with partial replacement. Hence, stratification that remains fixed across time should be avoided when monitoring populations that are likely to exhibit large changes in numbers and/or spatial distribution during the study period. Key words: bias; change estimation; monitoring; permanent plots; relative precision; sampling with partial replacement; temporary plots.

  15. Clustering analysis

    International Nuclear Information System (INIS)

    Romli

    1997-01-01

    Cluster analysis is the name of group of multivariate techniques whose principal purpose is to distinguish similar entities from the characteristics they process.To study this analysis, there are several algorithms that can be used. Therefore, this topic focuses to discuss the algorithms, such as, similarity measures, and hierarchical clustering which includes single linkage, complete linkage and average linkage method. also, non-hierarchical clustering method, which is popular name K -mean method ' will be discussed. Finally, this paper will be described the advantages and disadvantages of every methods

  16. Chemical Mixtures Health Risk Assessment of Environmental Contaminants: Concepts, Methods, Applications

    Science.gov (United States)

    This problems-based, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks from multic...

  17. Methods for the Determination of Chemical Contaminants in Drinking Water. Training Manual.

    Science.gov (United States)

    Office of Water Program Operations (EPA), Cincinnati, OH. National Training and Operational Technology Center.

    This training manual, intended for chemists and technicians with little or no experience in chemical procedures required to monitor drinking water, covers analytical methods for inorganic and organic chemical contaminants listed in the interim primary drinking water regulations. Topics include methods for heavy metals, nitrate, and organic…

  18. Chemical Mixtures Health Risk Assessment of Environmental Contaminants: Concepts, Methods, And Applications

    Science.gov (United States)

    This problems-based, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks from multic...

  19. Method of operating a thermal engine powered by a chemical reaction

    Science.gov (United States)

    Ross, J.; Escher, C.

    1988-06-07

    The invention involves a novel method of increasing the efficiency of a thermal engine. Heat is generated by a non-linear